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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

General Requirements for Designing and Implementing a Cryptography Module for Distributed Energy Resource (DER) Systems

Penetration of distributed energy resources (DERs) is rapidly increasing in the bulk power system (BPS); they are growing to be a significant portion of generation. As such, grid-support capabilities are being developed and implemented; IEEE Std. 1547 mandates new interconnection and interoperability standards to achieve these capabilities and allow remote users to change behaviors to many devices. However, as their presence increases, the impact of DERs on the BPS also increases. Therefore, if a disturbance occurs in the DER system, its effects could propagate throughout the BPS. These disturbances could range from equipment malfunctions to resource variability to cyber attacks. This document will discuss general requirements needed for developing a distributed cryptography module for implementation in DER systems. First, we will examine the composition of DER systems in Section 2. Procedures to identify critical assets and the security of DERs is discussed in Section 3. Section 4 introduces cryptography concepts and Section 5 discusses implementation needs and options. Finally, practical considerations are provided in Section 6 and conclusions are provided in Section 7.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A bi-level advanced control framework for large-scale control of buildings with system-level impact

Increased electricity consumption combined with new forms of generation is testing the reliability of our grid infrastructure. This work describes a method to improve the reliability of the grid through large-scale advanced building control. This paper develops a bi-level distributed control framework to shift the load of 153 buildings to achieve a system-level objective of tracking a power reference signal. This bi-level control is based on the previously-developed ANPV-MPC, a predictive controller that uses a Bayesian neural network to generate an accurate control model and adapt to changing conditions over time. By shifting the building electricity demand to better match the available power, the grid system supplying the buildings is more reliable as evidenced by the analysis of node voltages across an IEEE 13-bus distribution system. The proposed bi-level control framework tracks the system-level power reference with enough accuracy to regulate node voltages across the IEEE 13-bus distribution system within ANSI limits of ±5%. Additionally, the adaptive nature of ANPV-MPC allows each building across the system to adapt to changing conditions, further amplifying the system-level reliability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Characteristics of locational uncertainty marginal price for correlated uncertainties of variable renewable generation and demands

With the rapid increase of variable renewable energy sources in power systems, how to manage and price the uncertainty of renewable resources’ power outputs is becoming an urgent issue. Current market designs considering the uncertainties are mainly based on the probabilistic scenario set of demand and renewable energy resources power outputs. This consideration makes market designs vulnerable to three significant challenges when put into practice. First, the accurate probability distribution of renewable generation is hard to obtain in real-time. Second, it is challenging to clear the market timely with many scenarios to guarantee accuracy. Third, generation cost recovery cannot be guaranteed for some scenarios. To overcome these challenges, this paper proposes a locational uncertainty marginal price model to price the uncertainty explicitly based on a scenario-free stochastic market-clearing model. Instead of using the probabilistic scenario set, the uncertainty of renewable energy sources and loads is modeled with distributionally-robust chance constraints. The correlation of uncertainties can be endogenously modeled in both the market-clearing and the locational uncertainty marginal price formation. Furthermore, this paper proves that generation cost recovery, revenue adequacy, and partial market equilibrium can be achieved using the locational uncertainty marginal price model. Numerical results from both the small and large systems simulations validate that the generation cost recovery is maintained no matter the generation participates in uncertainty mitigation or not. The transmission congestion surplus is also allocated appropriately among loads, renewable energy sources, and financial transmission right owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Flexible dynamic boundary microgrid operation considering network and load unbalances

Flexible microgrids with dynamic boundaries have recently been introduced in the literature. With the ability to reconfigure the topology of the microgrids dynamically through remotely controlled switches, flexible microgrids with dynamic boundaries can further improve the resiliency and energy efficiency of microgrids with distributed energy resources (DERs). This paper focuses on the optimal operation considering one of the predominant characteristics of microgrids and distribution systems – unbalanced networks and loads. In existing literature, balanced modeling of microgrids is more common due to its attractive simplicity. The three-phase power unbalance has not been considered as a constraint on the generation units in a microgrid. Further, negative sequence constraints have also been neglected. In this article, we propose a set of constraints that is specifically related to the capabilities of inverter interfaced resources to supply unbalanced current/power when the microgrid is islanded from the main distribution grid. We incorporate the new set of constraints into two optimization formulations leveraging two convex relaxations of the three-phase power flow equations: mixed-integer linear programming (MILP) and mixed-integer semidefinite programming (MISDP) that optimize the dispatch of controllable switches and DERs in the microgrid. The algorithms are then extended to networked microgrids with grid-forming sources. We test the algorithms on a realistic community microgrid model in Puerto Rico as well as standardized IEEE distribution test feeders. The testing results demonstrate the performance of the proposed algorithms. The MILP is fast and scalable, and the MISDP enforces the negative sequence voltage constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Frequency Support of PMSG-WTG Based on Improved Inertial Control

With increasing integrations of large-scale systems based on permanent magnet synchronous generator wind turbine generators (PMSG-WTGs), the overall inertial response of a power system will tend to deteriorate as a result of the decoupling of rotor speed and grid frequency through the power converter as well as the scheduled retirement of conventional synchronous generators. Thus, PMSG-WTGs can provide value to an electric grid by contributing to the system's inertial response by utilizing the inherent kinetic energy stored in their rotating masses and fast power control. In this work, an improved inertial control method based on the maximum power point tracking operation curve is introduced to enhance the overall frequency support capability of PMSG-WTGs in the case of large supply-demand imbalances. Moreover, this method is implemented in the CART2-PMSG integrated model in MATLAB/Simulink to investigate its impact on the wind turbine's structural loads during the inertial response process. Simulation results indicate that the proposed method can effectively reduce the frequency nadir, arrest the rate of change of frequency, and mitigate the secondary frequency drop while imposing no negative impact on the major mechanical components of the wind turbine.

17 WIND ENERGY↗
DOE OSTI2016

Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamic Economic Dispatch Considering Transmission–Distribution Coordination and Automatic Regulation Effect

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately; the transmission–distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission–distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Scalable Optimization Methods for Distribution Networks With High PV Integration

Here this paper proposes a suite of algorithms to determine the active- and reactive-power setpoints for photovoltaic (PV) inverters in distribution networks. The objective is to optimize the operation of the distribution feeder according to a variety of performance objectives and ensure voltage regulation. In general, these algorithms take a form of the widely studied ac optimal power flow (OPF) problem. For the envisioned application domain, nonlinear power-flow constraints render pertinent OPF problems nonconvex and computationally intensive for large systems. To address these concerns, we formulate a quadratic constrained quadratic program (QCQP) by leveraging a linear approximation of the algebraic power-flow equations. Furthermore, simplification from QCQP to a linearly constrained quadratic program is provided under certain conditions. The merits of the proposed approach are demonstrated with simulation results that utilize realistic PV-generation and load-profile data for illustrative distribution-system test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Grid-Supportive Loads - A New Approach to Increasing Renewable Energy in Power Systems

This paper demonstrates the potential of inverter-based loads to support grid reliability during power system transients thereby enabling reliable integration of renewable energy in power systems. Such loads are referred to in this paper as grid-supportive loads (GSLs). A new GSL model is developed that simulates the transient response capabilities that can be programmed in electronic loads. The model’s design enables it to be easily integrated in widely used commercial power system transient analysis software. Theoretical expressions are derived that explain the workings of the GSL model. The performance, numerical stability, and impact of the GSL model is validated on 9-bus and 2000-bus synthetic power system models using generator tripping and bus fault disturbances. Results on the 2000 bus system show that in the absence of frequency support from wind/solar generation resources, just 20% of loads with grid-supportive capabilities can improve frequency response by up to 2000 MW/0.1 Hz and reduce deviation in frequency at nadir by up to 60% compared to the situation when GSLs are absent. Power system reliability also improves under fault events. Here, it is further shown that GSLs can aid in integrating more renewable generation without degrading the overall transient response of the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Reduced Mode Sapphire Optical Fiber and Sensing System

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Reduced Mode Sapphire Optical Fiber and Sensing System”. The objective of the five-year effort was to develop a low modal volume (LMV) single crystal sapphire fiber and demonstrate its advantages in current state-of-the-art sapphire-based temperature sensors and in novel distributed ultra-high temperature sensing systems. The project, sponsored by the Crosscutting Research Program, began in 2014 and had the original goal of developing the next generation of harsh environment sensing systems. After successfully completing the original scope of the award, the project was expanded and extended to allow for the development of harsh environment packaging and testing of a prototype sensor system. These novel fiber optic sensing technologies provide real-time, accurate, and reliable temperature measurements at distributed locations in existing coal-fueled electricity generating units to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. In the final year (2018) of the project, prototype sensing systems were successfully deployed and operated in small commercial coal and natural gas fired boilers at the Virginia Tech Power Plant. The harsh environment quasi-distributed temperature sensing technology was advanced from a (Technology Readiness Level) TRL=1 to a TRL=7 by demonstrating the full validation of the sensing system prototype in a relevant industrial environment. The real-time, accurate and reliable monitoring of temperatures at distributed locations is expected to lower operating costs by allowing more accurate measurement of the harsh conditions inside a boiler system to better control its operation. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to advance energy options to fuel our economy, strengthen our security, and improve the environment.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results are then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.

17 WIND ENERGY↗
DOE OSTI2024

Cognitive Grid Optimization

This project laid the foundation to include a security constrained economic dispatch (SCED) within one of the leading simulators which is used to train system operators who keep the lights on for over 150 million people in USA. The SCED is designed to handle very high penetrations of renewable generation as well as battery storage. As a follow on the this project, a Trusted Source Model of the North American Electric Interconnections will be built from public GIS data. The various North American Markets will be emulated. This Trusted Source Model will grow the software developers for the next generation of power applications that are needed to transition to all green generation while everything is electrified.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

NREL + Southern California Gas

NREL and Southern California Gas Company are evaluating a new 'power-to-gas' approach - one that produces methane through a biological pathway and uses the expansive natural gas infrastructure to store it. This approach has the potential to change how the power industry approaches renewable generation and energy storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Energy Systems Integration Partnerships: NREL + GINER ELX

At current levels of renewable generation there are already periods when the supply of electrical power significantly exceeds the level of demand. The wide penetration of renewable energy sources (RES) requires an energy storage solution which can include hydrogen generated via Polymer Electrolyte Membrane (PEM) electrolysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗