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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 307 records · Page 17
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DOE OSTI2025

IEEE PES GM Poster - Cyber-Informed Engineering Approach to Mitigating BESS Supply Chain Concerns

Battery energy storage systems (BESS) are increasingly important to meet the needs of grid resilience and reliability. BESS provide critical grid services, maintaining stability of the grid with increased variable conditions. However, there are significant geopolitical and security concerns regarding their operation in critical infrastructure, due to lack of a domestic supply chain and prevalence of foreign entity of concern (FEOC) components in BESS and associated inverter-based resources. The supply chain challenge is dually exacerbated by a lack of alternative suppliers who can meet the economic targets for energy delivery and a potentially adversarial supply chain. Solutions are needed to secure components, addressing mixed layers of risk and engineering controls. This paper presents a specific application of Cyber-Informed Engineering (CIE) principles for BESS and recommends an alternative strategy to blocking the supply chain, ensuring that grid modernization targets can be met despite lack of a validated or secure supply chain. This study focuses on the United State (U.S.) use case, but the process can be applied globally to address supply chain security challenges. CIE practices represent the next step in functional assurance and risk mitigation, ensuring optimal resource allocation and enhancing security measures to safeguard the future of energy in the U.S. and beyond.

25 - ENERGY STORAGE↗
DOE OSTI2025

Energy Sector Threat Brief: 2024 Round Up

What major and minor cybersecurity events affected the energy sector in the last year? What trends were observed in the events, disclosure of vulnerabilities, and other headline news? This talk will focus on real-world events put in the context of an evolving geo-political landscape. We will discuss events that had operational impact as well as events affecting third-parties with exploration of how the impact of incidents is changing as more stakeholders are involved in new projects and the complexity of the modern grid. We will focus on lessons learned from the 2024 trends that operators and their partners can apply to stay ahead of the threats in 2025.

14 - SOLAR ENERGY↗
DOE OSTI2025

A Rapid Procedure Development Approach for Multi-stage Validation of Novel Nuclear Power Plant Systems

The integration of renewable energy sources into the modern grid introduces variability in generation, challenging nuclear reactors to remain economically viable amid low wholesale electricity prices. To address this, Idaho National Laboratory?s Flexible Plant Operation and Generation program explores alternative revenue streams, including commoditizing excess thermal energy. A Thermal Power Dispatch (TPD) system enables steam extraction from the secondary loop for industrial uses like hydrogen production via high-temperature steam electrolysis.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

American Made Energy Infrastructure - Evolution of Federal Incentives and Requirements

This presentation, "Evolution of Federal Incentives and Requirements," explores the development and impact of federal cybersecurity regulations, tax credits, and domestic content requirements on the energy sector. It covers key legislation such as the ARRA of 2009, IIJA, and IRA, and their implications for grid modernization, manufacturing, and deployment of energy technologies. The presentation also addresses definitions and restrictions related to Foreign Entities of Concern (FEOC) and their impact on federal procurement. Additionally, it introduces the DOE's cybersecurity framework for energy supply chains and practical actions for compliance planning.

25 - ENERGY STORAGE↗
DOE OSTI2020

Distributed Conditions for Small-signal Stability of Power Grids and Local Control Design

Operating modern power grids with stability guarantees is markedly important. Typical methods for analyzing and certifying power grid stability are largely centralized relying on the ability of the system operator to gather network-wide information and accurately compute the system's eigenvalues. These methods are oftentimes not privacy-preserving and computationally burdensome. They are therefore, not well-suited to modern power grids where small-signal stability has to be evaluated timely, efficiently and in a privacy-preserving fashion. Herein, we introduce a distributed methodology for certifying small-signal stability of power grids and designing the local controllers. First, we analytically derive distributed conditions for network-wide stability that bus agents can inspect using local information. By leveraging these conditions, we then introduce a distributed control design algorithm (DCDA) that can guide the local control design so that stability of the interconnected system is guaranteed. The agents that adopt the proposed distributed algorithm are responsible for tuning their local controllers, producing their local control commands and ensuring that their local stability condition is met. The system operator is only responsible for verifying network-wide stability upon receiving affirmative responses from all agents and, announcing, that the overall system is stable. The proposed DCDA algorithm is numerically validated via simulations using the IEEE 39-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Co-Simulation of Detailed Whole Building with the Power System to Study Smart Grid Applications

Modernization of the power system in a way that ensures a sustainable energy system is arguably one of the most pressing concerns of our time. Buildings are important components in the power system. First, they are the main consumers of electricity and secondly, they do not have constant energy demand. Conventionally, electricity has been difficult to store and should be consumed as it is generated. Therefore, maintaining the demand and supply is critical in the power system. However, to reduce the complexity of power models, buildings (i.e., end-use loads) are traditionally modeled and represented as aggregated “dumb” nodes in the power system. This means we lack effective detailed whole building energy models that can support requirements and emerging technologies of the smart power grid. To gain greater insight into the relationship between building energy demand and power system performance, it is important to constitute a co-simulation framework to support detailed building energy modeling and simulation within the power system to study capabilities promised by the modern power grid. This paper discusses ongoing work at Pacific Northwest National Laboratory and presents underlying tools and framework needed to enable co-simulation of building, building energy systems and their control in the power system to study applications such as demand response, grid-based HVAC control, and deployment of buildings for ancillary services. The optimal goal is to develop an integrated modeling and simulation platform that is flexible, reusable, and scalable. Results of this work will contribute to future building and power system studies, especially those related to the integrated ‘smart grid’. Results are also expected to advance power resiliency and local (micro) scale grid studies where several building and renewable energy systems transact energy directly. This paper also reviews some applications that can be supported and studied using the framework introduced to understand their implications before they can be successfully implemented in the power system.

Makhmalbaf, Atefe↗
DOE OSTI2020

Distributed Solution Approach for a Stackelberg Pricing Game of Aggregated Demand Response

Demand-side management is a fundamental up-to-date strategy that transforms the traditional power grid to a modern smart grid where the flexible pricing mechanisms play a critical role in its successful implementation. In this paper, the pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is modeled as a Stackelberg game, where the DSO is the price maker that adjusts its strategy based on observed responses from LAs. With the concerns of computational cost and privacy protection, two distributed solution approaches, particle swarm optimization and pattern search algorithm, are conducted and compared with the classical centralized backward induction approach. Numerical results on a small case study demonstrate the effectiveness of the proposed distributed solution approaches in leveraging flexible demand response potential.

Chen, Yang↗
DOE OSTI2011

U.S. Department of Energy Report on the First Quadrennial Technology Review (QTR)

Access to clean, affordable, secure, and reliable energy has been a cornerstone of American’s economic growth. Yet, today the Nation’s systems that produce, store, transmit, and use energy are falling short of U.S needs. The Department of Energy’s (DOE) first Quadrennial Technology Review (QTR), launched at the recommendation of the President’s Council of Advisors on Science and Technology (PCAST), addresses these facts. The report details today’s energy landscape and the associated energy security, economic and environmental challenges; provides a framework for presenting six strategies to address those challenges encompassing vehicle efficiency, deployment of alternative hydrocarbon fuels, increased building and industrial efficiency, modernization of the grid, and deployment of clean electricity; addresses priorities among activities in DOE’s energy-technology programs; and explains the roles that DOE, the broader government, the private sector, the national laboratories, and academia play in energy transformation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Voltage Service Limits Smart Contract Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Generator

Modern electrical grids face growing stability risks from customer-owned generators, especially at points of common couplings (PCCs). Disruptive behavior from power-electronic sources can cause protective relays to isolate problematic generators, making measurement integrity critical. This article presents a distributed ledger technology (DLT) approach that uses smart contracts to evaluate PCC voltage measurements and trigger backup breaker operations. The approach is framed as a verifiable, multi-organization attestation and audit layer, not as a real-time control security mechanism. In the proposed architecture, voltage measurements from a hardware protective relay are anchored on a DLT through the Cyber Grid Guard (CGG) system for attestation by both the grid utility and customer-owned generator. A Voltage Service Limits (VSLs) smart contract evaluates the on-chain measurements against allowable phase-voltage limits derived from the ANSI C84.1 standard. The framework is validated in a hardware-relay-in-the-loop test bed under sustained-undervoltage, sustained-overvoltage, and transient line-to-line fault scenarios. The results show that the VSL smart contract can process these measurements and issue backup breaker actions consistent with the defined service-limit criteria, demonstrating the DLT potential as a verifiable audit layer at the PCC that complements primary protection.

cyber security↗
DOE OSTI2023

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗
DOE OSTI2020

Determining the Reaction Time for Triggering Supportive Control Actions to Guarantee Adequate Frequency Response in Smart Grids

The progressive integration of renewable energy resources in the modern power grid can result in unsatisfactory frequency responses. To address this problem, wind turbine generators (WTGs), in particular, can be employed to support the power grid. Most works, however, only consider a simple step disturbance. In this paper, a new class of worst-case disturbances is introduced and their nefarious impact on renewable-penetrated power systems is investigated. The worst-case disturbances are derived using optimal control theory. More importantly, the proposed mechanism allows to determine the reaction time to trigger supportive control actions of WTGs to ensure satisfactory frequency response. Numerical results are provided and the effects of the worst-case disturbance on the reaction time are presented.

Luo, Jiecai↗
DOE OSTI2019

Demand Response for Thermal Fairness in District Heating Networks

District Heating (DH) networks are complex thermal grids wherein a centrally heated fluid is circulated through a network of pipes and heat exchangers to meet the heating needs of residential and commercial buildings. Several factors can lead to inefficient and unfair energy distribution among consumers in these networks. These include varying levels of building insulation, distance of individual buildings from the central energy source, and thermal losses in network pipes. Moreover, shortage of energy at the central energy source and extreme weather conditions can exacerbate these issues, leading to differing levels of thermal comfort and customer disgruntlement in the long run. In this paper, we propose and study a demand response scheme that attempts to ensure thermal fairness among energy consumers in modern thermal grids. We develop optimization formulations based on thermodynamic models of DH networks, which determine optimal energy flow for individual buildings in order to achieve thermal fairness across the network. Our experimental results using physics based models for DH networks show that it is possible to achieve network level thermal fairness based social welfare objectives by controlling network parameters such as mass flow rates of water to the consumer premises and the supply water temperature, even when some network parameters like building thermal characteristics remain unknown.

Bhattacharya, Saptarshi↗
DOE OSTI2019

Physics-Guided Deep Learning for Time-Series State Estimation Against False Data Injection Attacks

The modern power grid is a cyber-physical system. While the grid is becoming more intelligent with emerging sensing and communication techniques, new vulnerabilities are introduced and cyber security becomes a major concern. One type of cyber-attacks - False Data Injection Attacks (FDIAs) - exploits the limitations in traditional power system state estimation, and modifies system states without being detected. In this paper, we propose a physics-guided deep learning (PGDL) approach to defend against FDIAs. The PGDL takes real-time measurements as inputs to neural networks, outputs the estimated states, and reconstructs measurements considering power system physics. A deep recurrent neural network - Long Short-Term Memory (LSTM) - is employed to learn the temporal correlations among states. This hybrid learning model leads to a time-series state estimation method to defend against FDIAs. The simulation results using IEEE 14-bus test system demonstrate the accuracy and robustness of the proposed time-series state estimation under FDIAs.

Cyber security, state estimation, physics-guided d↗
DOE OSTI2024

Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks

Large-scale multiphysics simulations are computationally challenging due to the coupling of multiple processes with widely disparate time scales. The advent of exascale computing systems exacerbates these challenges since these systems enable ever-increasing size and complexity. In recent years, there has been renewed interest in developing multirate methods as a means to handle the large range of time scales, as these methods may afford greater accuracy and efficiency than more traditional approaches of using implicit-explicit (IMEX) and low-order operator splitting schemes. However, to date there have been few performance studies that compare different classes of multirate integrators on complex application problems. In this work, we study the performance of several newly developed multirate infinitesimal (MRI) methods, implemented in the SUNDIALS solver package, on two reacting flow model problems built on structured mesh frameworks. The first model revisits prior work on a compressible reacting flow problem with complex chemistry that is implemented using BoxLib but where we now include comparisons between a new explicit MRI scheme with the multirate spectral deferred correction (SDC) methods in the original paper. The second problem uses the same complex chemistry as the first problem, combined with a simplified flow model, but runs at a large spatial scale where explicit methods become infeasible due to stability constraints. Two recently developed IMEX MRI multirate methods are tested. These methods rely on advanced features of the AMReX framework on which the model is built, such as multilevel grids and multilevel preconditioners. The results from these two problems show that MRI multirate methods can offer significant performance benefits on complex multiphysics application problems and that these methods may be combined with advanced spatial discretization to compound the advantages of both.

97 MATHEMATICS AND COMPUTING↗