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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 163 records · Page 9

Control of energy storage to reduce electric power system off-nominal frequency deviations

A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.

Vartanian, Charles K.↗

Considerations for a Medium-Voltage DC Electrolysis Testbed

Here we present the results of a study focused on the feasibility of using Medium Voltage DC (MVDC) power distribution from wind power generation to electrolyzers for hydrogen production. This approach, using hybrid energy generation in a MVDC microgrid, offers many advantages. These include possible improvements in efficiency, reliability and installation cost compared to a more typical state-of-the-art AC distribution configuration. It also eliminates the need for transformers, which have recently been subject to price volatility and availability concerns. This study highlights the practical feasibility of MVDC distribution networks for integrating various energy sources, offering improved efficiency and reduced system complexity compared to conventional AC-based solutions. Future work will focus on enhancing fault protection strategies, scaling the system to larger renewable installations, and conducting hardware implementation at the National Renewable Energy Laboratory's (NREL) Flatirons Campus (FC). In the sections that follow we show that a DC Collection and Distribution System (DC CDS) reduces the losses associated with the electrical conversion / distribution process relative to a state-of-the-art AC approach, improving overall efficiency by 5%. On the qualitative side, reducing the number of conversion stages is likely to improve reliability, reduce capital investment cost, and enable simpler control algorithms to be used, and reduced risk of instabilities and malfunctions.

08 HYDROGEN↗

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Three-Phase Microgrid Restoration Model Considering Unbalanced Operation of Distributed Generation

Recent severe outages highlight the urgency of improving grid resiliency in the U.S. Microgrid formation schemes are proposed to restore critical loads after outages occur. Most distribution networks have unbalanced configurations that are not represented in sufficient detail by single-phase models. This study provides a microgrid formation plan that adopts a three-phase network model to represent unbalanced distribution networks. The problem formulation has a quadratic objective function with mixed-integer linear constraints. The three-phase network model enables us to examine the three-phase power outputs of distributed generators (DGs), preventing unbalanced operation that might trip DGs. Because the DG unbalanced operation constraint is non-convex, an iterative process is presented that checks whether the unbalanced operation limits for DGs are satisfied after each iteration of optimization. We also develop a relatively conservative linear approximation on the unbalanced operation constraint to handle larger networks. Compared with the iterative solution process, the conservative linear approximation is able to accelerate the solution process at the cost of sacrificing optimality to a limited extent. Simulation in the IEEE 34 node and IEEE 123 test feeders indicate that the proposed method yields more practical microgrid formations results. In addition, this paper explores the coordinated operation of DGs and energy storage (ES) installations. The unbalanced three-phase outputs of ESs combined with the relatively balanced outputs of DGs could supply unbalanced loads. In conclusion, the case study also validates the DG-ES coordination.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids

The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distribution systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. Furthermore, the SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Coordination of Energy Storage and Distributed Generation for Voltage Control and Peak-valley Filling

The increasing penetration of distributed energy resources (DERs) in distribution network (DN) poses challenges on voltage control. In addition, the growing integration of DERs also reshapes the traditional load profile. To comprehensively address the voltage control and peak-valley filling in DN, this paper proposes a model predictive control (MPC) based optimization framework. The proposed method can achieve coordinated voltage control and peak-valley filling by adjusting the reactive power output from distributed generations (DGs) and the charging/discharging of energy storage systems (ESS). The performance of the proposed method is demonstrated by simulations on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗

Distributed Energy Planning for Climate Resilience

At various levels of government across the United States and globally climate resilient solutions are being adopted and implemented. Solutions vary based on predicted hazards, community context, priorities, complexity, and available resources. Lessons are being learned through the implementation process, which can be replicated regardless of level or type of government entity carrying out the resiliency planning. Through a number of analyses and technical support across the world, NREL has learned key lessons related to resilience planning associated with power generation and water distribution. Distributed energy generation is a large factor in building resilience with clean energy technologies and solutions. The technical and policy solutions associated with distributed energy implementation for resilience fall into a few major categories, including spatial diversification, microgrids, water-energy nexus, policy, and redundancy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗

Virtual Agents-Based Attack-Resilient Distributed Control for Islanded AC Microgrid

Due to its dependence on a communication network, distributed secondary control of microgrids is susceptible to denial-of-service (DoS) attacks in channel shutdown mode, which may negatively impact the network connectivity and thus deteriorate the coordination and power sharing among distributed generators (DGs). Honeypot is a common method for cyber deception by introducing fake targets. However, in the context of microgrid, the misleading information spread by honeypots will also impact the system performance. This paper proposes an attack-resilient distributed control for AC microgrids utilizing virtual agents (VAs) to counteract both DoS edge and node attacks. The VAs are designed to not impact the system’s steady state during normal operation but to share information among neighboring real agents and serve as dummy targets for DoS attacks. The control with VAs is implemented by a primal-dual gradient based distributed algorithm to efficiently obtain a practical solution for voltage/frequency regulation and power sharing. The simulation results on a 4-DG test system and a modified IEEE 34-bus system show that 1) VAs do not impact the normal functionality of the test system, and 2) deploying VAs can enhance the resilience of the microgrid control against DoS edge and node attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fault-tolerant power-distribution modules for a power plant

Embodiments are directed to fault-tolerant power-distribution modules (PDM). A PDM is included in a power plant to provide a portion of the power generated by the plant as a direct current (DC) signal for the operation of the plant. A power-distribution system distributes a portion of the power generated by the plant to one or more PDMs, as an alternating current (AC) signal. The PDMs provide electrical power to various plant loads. The plant loads may be related to the safety of the operation of the power plant. At least one of the plant loads is a non-safety related load. A PDM may be a DC power supply. The power plant may include one or more power-generating module (PGM) assemblies. At least one of the PGM assemblies may include a nuclear reactor. Accordingly, the power plant may be a modular nuclear power plant.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Equivalent Time-Variant Storage Model to Harness EV Flexibility: Forecast and Aggregation

The demand for vehicle charging will necessitate large investments in power distribution, transmission, and generation. However, this demand is often also flexible in time, and can be actively managed to reduce the needed investments, and to better integrate renewable electricity. Harnessing this flexibility requires forecasting and controlling electric vehicle (EV) charging at thousands of stations. In this work, we address the problem of forecasting and management of the aggregate flexible demand from tens to thousands of EV supply equipment (EVSEs). First, it presents an equivalent time-variant storage model for flexible demand at an aggregation of EVSEs. The proposed model is generalizable to different markets, and also to different flexible loads. Model parameters representing multiple EVSEs can be easily aggregated by summation, and forecasted using autoregressive models. The forecastability of uncontrolled demand and storage parameters is evaluated using data from 1341 nonresidential EVSEs located in Northern California. The median coefficient of variation is as low as 24% for the forecast of uncontrolled demand at the highest aggregation and 10-15% for the storage parameters. The benefits of aggregation and forecastability are demonstrated using an energy arbitrage scenario. Purchasing energy day ahead is less expensive than in the real-time market, but relies on a uncertain forecast of charging availability. The results show that the forecastability significantly improves for larger aggregations. This helps the aggregator make a better forecast, and decreases the cost of charging in comparison to an uncontrolled case by 60% with respect to an oracle scenario.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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↗

Thermophotovoltaic Heat Engine

This project was aimed at developing a thermophotovoltaic device that efficiently converts thermal radiation to electrical power. Historically, TPV devices have been plagued by poor robustness; this project sought to overcome this by merging innovations in nanophotonics, photovoltaics, and robust thermal engineering. Efforts were focused on developing high efficiency TPV devices which may drastically alter the electricity sector by enabling efficient (> 20%), fuel-flexible (any combustion fuel), distributed (< 10 kW) power generation. The project research identified the technical performance limits, technology differentiator, and customer value proposition for TPV devices and established technical performance requirements for a minimum viable product.

30 DIRECT ENERGY CONVERSION↗

A Modular Heat Engine for the Direct Conversion of Natural Gas to Hydrogen and Power using Hydrogen Turbines (Phase I Final Report)

This report describes a novel, modular heat engine comprising of a one-step hydrogen production from natural gas with in-situ CO 2 separation which is amenable for re-use or sequestration. Combining with a hydrogen turbine subsystem, a distributed or central power generation system is conceived. An added hydrogen storage subsystem enables load-following capability. The techno-economics of the overall system compared favorably against current state-of-the-art natural gas combined cycle plants with post-combustion CO 2 capture.

01 COAL, LIGNITE, AND PEAT↗

A Systematic Approach to Light Load Calculation for DG Un-Intentional Islanding

With the influx of distributed generation (DG) penetration, power utilities have adopted active anti-islanding protection methods to prevent an unintentional islanding condition. One commonly used protection scheme is implemented through the use of a transfer trip from the upline connected substation to the DG facility and is required when the capacity of connected DGs exceed a certain threshold of local minimum load. The threshold established by standard IEEE 1547.2-2009 states that a 3:1 minimum load to generation ratio is acceptable to ensure the DG will not sustain an unintentional island. However, the term “minimum load” is not precisely defined in any standard, and in practice, a light load value is chosen by engineers through manual methods that can be inconsistent, not representative and change drastically based on various cases. To solve this problem, this paper proposes a new light load calculation method creating consistency and better accuracy; the method has been implemented in. NET C# application and is used within Dominion Energy.

Chen, Le↗

Companion Assisted Software Based Remote Attestation in SCADA Networks

Critical infrastructure such as power generation and water distribution systems have become a priority target in cyber warfare because of their recent computerization and introduction to the internet. As a result, Supervisory Control and Data Acquisition (SCADA) system security has become a hot topic in academic and industrial research. Among these topics, Remote Attestation is a security method intended to detect the presence of fileless malware in remote devices as they continue to operate. This allows for the detection of malware in the absence of long-term storage artifacts before symptoms of compromise begin to appear. In general, a trusted device (the verifier) makes a request for evidence of innocence from the untrusted device (the prover). In software-based schemes, the verifier can then measure the delay between its request and the prover’s response. If this delay is greater than the known computational time of the evidence gathering algorithm performed by the prover, then evidence may have been forged. Multi-hop networks often introduce too much network jitter to allow accurate measurement of prover response time, which limits the effectiveness of software based Remote Attestation in a real-world setting. In this work, we introduce a companion device that the verifier can trust to perform a subset of attestation, thereby removing any network jitter. This device is a Field Programmable Gate Array (FPGA) that is physically connected to the prover. We provide a communication protocol between the verifier, prover, and companion. To evaluate our scheme, we simulate it in a common SCADA network environment under normal and heavy traffic loads. Our simulations are performed in the discrete event network simulator NS-3, and we perform statistical analysis over our results to show that our scheme allows for tight timing constraints to be placed on the prover such that the verifier can more easily determine the validity of the evidence that it receives.

Johnson, William A.↗

Industrialized and Robotic Construction Advances in Terrestrial Construction and Opportunities in Space Construction

Advanced Building Construction (ABC) methods such as industrialized prefabrication and robotically controlled additive deposition are becoming promising technologies to support rapid construction of buildings at volume and scale. However, apart from the structural shell of the building, optimal integration of other systems – mechanical, electrical, plumbing, thermal, power generation, storage and distribution, is key to enabling functional buildings. Leveraging ABC methods to integrate such systems in the buildings requires the building design to be optimized for constructability constraints imposed by the industrialized and robotically controlled production setups entailing such ABC methods. The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been focusing on research and development of such ABC technologies and processes that can lead to production of buildings which are resilient to extreme climatic conditions at reduced cost and time. There is a potential synergy between such advancements in terrestrial construction, which can be leveraged for the benefit of space (orbital and extra-terrestrial) construction. Similarly, advances in space construction can lend itself to accelerated adoption of robotic construction methods in terrestrial construction. This presentation will give an overview of selective research efforts of the ICI team at NREL, along with a vision for potential collaborations with agencies like NASA.

3D printing↗