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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Robust Communication-Free Protection Scheme for Islanded Microgrids with Relay Logic and Hardware-in-the-Loop Validation

This paper presents the Imbalance Square Factor (ISF) detection algorithm, an effective, computationally lightweight method for detecting faults in inverter-based microgrids. ISF provides a high magnitude at the time of the fault, which allows for fast detection and coordination between primary and backup relays. The imbalance squared factor, calculated using local voltage and currents, is used for fault detection and coordination among three relays. ISF is validated in hardware-in-the-loop (HIL) implementation inside commercial-grade relay logic (SEL-751). The HIL validation shows that ISF can coordinate primary, secondary, and tertiary relays in the 13-bus system in islanded operation.

Ferrari Maglia, Max [ORNL]↗
DOE OSTI2025

Integration of Electrolysis Systems Into Isolated Microgrid Systems at Extreme Cold Climates

Isolated microgrid systems are generally used to power communities in remote locations where transmission line installations are cost prohibitive. These systems are usually powered by diesel generators, delivering expensive energy with high carbon emissions. However, most of these communities have special geographic access to renewable energy. These special conditions make it interesting to investigate the deployment of renewable energies and storage solutions. Within this scope, this paper analyses the integration of water electrolysis systems into off-grid communities, simulating the electrolyzer as well as the whole electrical grid in real time.

digital real-time simulation↗
DOE OSTI2024

Improved microgrid resiliency through distributionally robust optimization under a policy-mode framework

Critical energy infrastructure are constantly under stress due to the ever increasing disruptions caused by wildfires, hurricanes, other weather related extreme events and cyber-attacks. Hence it becomes important to make critical infrastructure resilient to threats from such cyber-physical events. However, such events are hard to predict and numerous in nature and type and it becomes infeasible to make a system resilient to every possible such cyber-physical event. Such an approach can make the system operation overly conservative and impractical to operate. Furthermore, distributions of such events are hard to predict and historical data available on such events can be very sparse, making the problem even harder to solve. To deal with these issues, in this paper we present a policy-mode framework that enumerates and predicts the probability of various cyber-physical events and then a distributionally robust optimization (DRO) formulation that is robust to the sparsity of the available historical data. The proposed algorithm is illustrated on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources (DERs) and energy storage. Simulations are carried to validate the resiliency metrics under the sampled disruption events.

Nazir, Mohammad Nawaf↗
DOE OSTI2024

Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

R pesante colón, Marcos↗
DOE OSTI2024

On the Use of Tidal Power for Enhancing Power System Resilience with Networked Microgrids

The resilience of a power system to withstand a high-impact low-frequency event is a growing concern, especially in coastal communities that tend to be densely populated and very prone to extreme events such as storms and flooding. In such areas, marine renewable energy can be integrated with the existing renewable energy sources to improve generation diversity and power system resiliency. Using networked microgrids as an example, this paper proposes an empirical study to investigate the impact of marine resources, in particular, tidal energy on the power system resiliency. A set of quantitative metrics with intuitive physical interpretations is used to evaluate the resiliency of a power system that is enhanced with distributed generation in the form of rooftop photovoltaic systems and tidal generators. The effectiveness of resource diversification on the power system resiliency is demonstrated through simulations on a model of a real-world coastal distribution feeder located in Sequim, Washington.

Peerzada, Aaqib A.↗
DOE OSTI2025

Reinforcement Learning-Based Secondary Control Strategy for Voltage and Frequency Regulation in Islanded Inverter-Based Microgrids

This paper presents a reinforcement learning (RL) approach for secondary voltage and frequency control in islanded inverter-based microgrids. The proposed control strategy aims to restore voltage and frequency deviations caused by the primary droop control while ensuring proper power sharing between distributed generators. The RL agent is designed to provide correction signals to the primary control, considering communication delays and system constraints. The effectiveness of the proposed control strategy is validated through simulation results in MATLAB/Simulink environment, demonstrating superior performance in maintaining voltage and frequency within the nominal values.

Rodriguez Martinez, Omar Felipe [University of Pue↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Robust Frequency and Voltage-Constrained Networked Microgrid Restoration

Here, this paper proposes a safe soft actor-critic reinforcement learning (RL) algorithm–based controller for networked microgrid restoration. It formulates the post black-start start as a finite-horizon constrained Markov decision process. The RL agent co-optimizes real and reactive power set-points for both grid-forming and grid-following inverters under explicit voltage and frequency constraints, while enforcing proper power sharing via the Mean Active Power Sharing Index (MPSI) and Mean Reactive Power Sharing Index (MQSI). Numerical results obtained on the IEEE 123-bus distribution system show that the proposed method achieves a mean voltage build-up time of 0.01 s without breaching the 5% sharing-violation budget under various load scenarios, considering MPSI and MQSI indices. These findings demonstrate that the proposed method yields fast and safe black-start schedules without resorting to heuristic penalties.

Selim, Alaa [Dartmouth College, Hanover, NH (Unite↗
DOE OSTI2024

Advanced Protection for Microgrids and DER in Secondary Networks and Meshed Distribution Systems

Although there are increasing numbers of distributed energy resources (DERs) and microgrids being deployed, current IEEE and utility standards generally strictly limit their interconnection inside secondary networks. Secondary networks are low-voltage meshed (non-radial) distribution systems that create redundancy in the path from the main grid source to each load. This redundancy provides a high level of immunity to disruptions in the distribution system, and thus extremely high reliability of electric power service. There are two main types of secondary networks, called grid and spot secondary networks, both of which are used worldwide. In the future, primary networks in distribution systems that might include looped or meshed distribution systems at the primary-voltage (medium-voltage) level may also become common as a means for improving distribution reliability and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Supercapacitor-Based Power Resilience Solutions for Modern Grids, Microgrids, and Facilities

This report summarizes the tests and results of a supercapacitor based energy storage system demonstration project performed in collaboration with Capacitech Energy, Orlando Utilities Commission and Sandia National Labs. This project evaluated a 3.6 farad (F), 720 V rated supercapacitor system in a microgrid environment to study three primary use cases: black start, voltage regulation, and load leveling, and successfully demonstrated the performance for the use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Optimally sited microgrids for energy resilience in Mount Desert Island, ME

Mount Desert Island (MDI) (≈110 sq mi; ≈10,000 year‑round residents) is located on the eastern coast of Maine. Acadia National Park is located on the island, protecting 47,000+ acres of land which draws millions of visitors annually. The island is divided into four towns (Tremont, Southwest Harbor, Mount Desert, Bar Harbor). The island’s distribution system is supplied by a single 35‑kV mainland feeder and a mix of aging distribution components; outage exposure is not uniform across the island. Residents fear that outage events are starting to exceed resilience expectations. MDI community leaders asked Sandia National Laboratories to characterize energy system vulnerability and to develop conceptual microgrid solutions that improve community resilience while also producing co‑benefits for reliability, access, and sustainable development.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Microgrid for Lunar Surface Power

Sustained lunar surface operations will require access to continuous and highly reliable power to support mission needs and an ability to evolve and grow over time (years). The first initial loads that arrive on the lunar surface will contain their own dedicated power sources. Over time, as the lunar surface operations and power demands grow, these individual power loads will require more power than can be generated with any single power device. This demand drives the need for inter-connecting loads and power devices to share power between them, resulting in a micro-grid. One advantage of developing a lunar surface micro-grid is that it will allow lunar surface operations to resemble electrical utility operations on Earth; it allows power to be generated where it is convenient and allows power to be consumed where it is convenient and required. The micro-grid concept also provides another benefit of affording the ability to increase overall system reliability by integrating dissimilar power generation and energy storage devices together, for example modifying the power generation strategy to include both solar arrays and nuclear. This talk provides an overview of NASA’s interest in developing a lunar microgrid and provides areas where external entities can play a role in developing futuristic power needs.

Jeffrey Csank↗
NASA NTRSDate not supplied

Hierarchical Control of Distributed Battery Energy Storage System in a DC Microgrid

This paper presents a novel hierarchical control approach of a DC microgrid (DCMG) which is supplied by a distributed battery energy storage system (BESS). With this approach, all battery units distributed in the BESS can be controlled to discharge with accurate current sharing and state-of-charge (SoC) balancing. Similar to other hierarchical control approaches used in DCMGs, this approach consists of three levels: (1) primary control, (2) secondary control and (3) tertiary control. This work includes defining a unit control error (UCE) at the secondary control level and evaluating current sharing weights at tertiary control level. A centralized controller at secondary control level is designed to detect the UCEs of each battery unit, and to restore the average voltage of a DCMG and control battery current sharing simultaneously. The distributed battery units share the load current in a DCMG based on weights. These weights are evaluated at the tertiary control level based on battery SoCs. The approach’s effectiveness was confirmed in digital simulation tests with the same simulation model as used in the NASA AMPS Modular Hardware Emulator.

Jing Zhang↗
NASA NTRSDate not supplied

Hierarchical Control of Distributed Battery Energy Storage Systems in a DC Microgrid

Contents - NASA Future Power Systems - DC Microgrid with Distributed Battery Energy Storage - A simplified gateway power system - Droop Control (Primary Control) - Distributed battery units, droop control, and load sharing characteristics - Simulation results - Three-Level Hierarchical Control of Distributed Battery Units During Eclipse - Secondary Control - Objective and definition of unit control error - Implementation of secondary control - Simulation results - Tertiary Control - Schedule BU current sharing with the objective of equal SoC - Simulation results•Conclusions

Jing Zhang↗
DOE OSTI2024

DC Microgrid Reliability Enhancement with Adaptive Converter Thermal Management

Due to the different device selections, aging levels, and thermal dissipation performance, some converters may take additional thermal stress on switching devices than others in paralleled converter systems, which will reduce system reliability. To address this problem, this paper proposes a power-sharing strategy with adaptive thermal management. First, the temperature-based power loss model and electrical-thermal model are established. Based on that, a high-accuracy IGBT junction temperature estimate considering the power loss-temperature coupling can be achieved. Further, the thermal-sharing for all the switching devices in paralleled converters can be achieved with the proposed adaptive thermal management strategy. The proposed strategy can change the power-sharing ratio adaptively according to the system operation conditions, which will contribute to the system reliability enhancement. The effectiveness of the proposed strategy is verified through PLECS thermal simulation and joint real-time simulation with Dspace and RT-box.

DC microgrid↗