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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Study on Conversion from an Existing Alternating Current Medium-Voltage Line to a Direct Current Line: A Case of Load or Source Expansion

Simultaneous increase of power generation through renewable systems and load due owing to the rapid growth in electrified road transportation systems, leads to new challenges in the design, operation, and protection of distribution-level electrical power systems. This paper addresses challenges related to the integration of new sources or loads to a distribution grid through long alternating current lines. The International Council on Large Electric Systems medium-voltage benchmark model developed for North America was used for simulation studies. Use cases were developed to illuminate the issues related to long alternating current lines and the usefulness of medium-voltage direct current lines in a distribution network.

Jaldanki, Sreenivasa↗
DOE OSTI2021

OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)

Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim

Blonsky, Michael↗
DOE OSTI2023

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

DC distribution↗
DOE OSTI2026

Cybersecurity Risk Profiles for Distributed Energy Resource Management Systems

Managing the digitalization of increasingly diversity energy resources is a complex challenge for energy systems planners and managers. As the penetration of solar photovoltaics (PV) and other distributed renewable energy resources (DERs) expands, distributed energy resource management systems (DERMS) will play an increasingly important role in managing, monitoring, and controlling DERs as electric systems before more distributed, interconnected, and networked. However, the cybersecurity implications of DERMS deployments are not well understood today. A lack of understanding around the cybersecurity implications of DERMS deployments and variability in the security posture of DERMS vendors, owners, and operators could introduce new security risks to evolving electric power systems. This paper describes cybersecurity attack scenarios on DERMS, identifies related cybersecurity standards and guidelines, reviews the security features of state-of-the-art DERMS solutions, and offers cybersecurity guidance for DERMS vendors, owners, and operators to protect DERMS' unique capabilities. Standardizing cybersecurity requirements for DERMS could help improve the security of DERMS integrations and improve innovations that are more secure by design. The cybersecurity guidance found in this paper is intended to offer a unified approach and lay the foundation for future standardization of DERMS cybersecurity to reduce risk to the solar industry and other renewable energy stakeholders when integrating these technologies with electric power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Development and Evaluation of Distributed Energy Resource Device Models: Electric Vehicles, Electric Water Heaters, and Commercial Refrigeration Systems

In order to validate distributed energy resource (DER) models operated with grid services in the GMLC 1.4.2 team’s February (GMLC 2019a) and July (GMLC 2019b) reports, a test and measurement program using actual DER devices was conducted by national laboratories for three devices: (1) electric vehicles (EVs), (2) water heaters, and (3) commercial refrigeration. Test procedures were developed and carried out to identify the mathematical models and their parameters that describe the operational function, characterize the physics, and obey transient response of the devices. This report focuses on the experimental results obtained to develop and verify simulations of three specific EV models. This section summarizes elements of the mathematical model and shows the necessity data collected from the EVs while charging and discharging (driving). In the course of the study, we found it necessary to make some modifications to the model to deal with observed transient behavior. Section 1.2 details the model assumptions and equations, Section 1.3 provides details of the EVs tested, Section 1.4 outlines the test procedures developed for the projects, and Section 1.5 presents the experimental results obtained for the three different EVs tested and how these results compare to the models running the same test profiles.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
DOE OSTI2021

There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure

In March 2021, the cumulative sale of plug-in electric vehicles (PEVs), including plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV), reached 1.8 million in the United States (Argonne National Laboratory 2021). However, PEV adoption is still in its infancy; its market share has just reached around 3% of new light-duty vehicle (LDV) sales by the end of 2020 (Alliance for Automotive Innovation 2021). Current trends suggest that PEV market share in the United States is increasing. The U.S. Energy Information Administration's (EIA's) 2020 Annual Energy Outlook forecasts PEV registrations to exceed 8 million vehicles by 2030 (AEO 2020). PEV adoption is expected to be led by states that are regulating the sale of zero emission vehicles (ZEVs) (California Air Resources Board). California continues to push for more aggressive ZEV regulations; the state recently issued an executive order aimed at 100% of LDV sales being ZEVs by 2035 (Office of Governor Newsom). At the federal level, the Biden administration has shown great ambition in encouraging broader electric vehicle (EV) adoption, including setting the goal of installing 500,000 new chargers nationwide (The White House 2021). Access to charging infrastructure is consistently cited as one of the primary barriers to the increased sale of PHEVs and BEVs (Carley et al. 2019). In the United States, PEV charging options are often described using a pyramid structure, with residential charging as the foundation, workplace charging in the middle, and public charging on top (Figure 1). The existing electricity system, which generates, transmits, and distributes electric fuel to residential households, has helped PEVs partially overcome the "chicken and egg" conundrum that has haunted other alternative fuels. Viable home access to electric charging is also an important equity issue, because non-residential PEV charging options (e.g., workplace or public charging stations) are generally more expensive. Households without residential charging access may experience higher total cost of PEV ownership if non-residential charging options are more costly.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Distributed Wind Resilience Metrics for Electric Energy Delivery Systems: Comprehensive Literature Review

While most people have a general concept of what it means to be “resilient,” an examination of definitions from different sources reveals that there are key commonalities but key differences as well. The lack of a generally accepted definition and application of resilience extends to electric energy delivery systems. Without an accepted definition, it is difficult to implement programs or processes to improve resiliency. In this paper, existing work from industry, regulatory bodies, and national laboratories to define and apply resilience to electric energy delivery systems is studied to understand the key components to define resilience and better understand associated metrics. This understanding is then applied to distributed wind for a specific example of how resilience of a system is affected by the technologies and generation sources used to support it. A key finding is that there is no “one size fits all” process for resilience. Each system has a “distinctiveness” characteristic, which qualifies the possibility of differences in resilience due to different threats, geography, stakeholders, risk tolerance, and mitigations. The distinctiveness characteristic extends to distributed wind, where different configurations may lend the distributed wind to contribute to the resilience of systems in a variety of ways. The findings of this research demonstrate the need for a resilience framework that can be readily applied by stakeholders to improve resilience based on the specific system, threat, risk tolerance and stakeholders.

17 WIND ENERGY↗
DOE OSTI2026

Effectively Considering the Distribution System in Integrated Resource Plans

While electricity planning practices vary by state and utility based on utility type and market structure, integrated resource planning (IRP) remains a prominent vehicle — even in states with centrally-organized wholesale electricity markets. IRP focuses on meeting forecasted long-term electricity needs. Typically, utilities have not considered impacts of design and operation of the low-voltage distribution network in IRP. With advanced capabilities of grid-edge technologies to generate and store electricity and provide load flexibility, and large utility investments in distribution systems, it's increasingly important to consider at least some distribution planning elements in IRP. This report considers the value proposition for doing so, such as reducing utility costs through resource co-optimization and strategic siting of grid-edge resources, and idenfities the most important touchpoints between planning for bulk power and distribution systems and provide a range of tactics for integrating these two processes.

Relf, Grace [Lawrence Berkeley National Laboratory↗
DOE OSTI2023

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗
DOE OSTI2023

Impact Analysis of Future Electric Vehicles Using Model of Real Distribution Feeders

Globally, the number of electric vehicles (EVs) continues to increase. This on-going trend poses challenges for power distribution systems. The inclusion of electric vehicle supply equipment (EVSE) should be compatible with a changing energy system, whose structure is becoming increasingly distributed. The impact of future EVs should be analyzed and considered in the system planning and upgrades. In this study, impact analysis of future EVs is conducted for a utility company of U.S. West Coast. Real data of distribution feeders is converted into the GridLAB-D model for running power flow analysis. An estimation of the additional loading of EVs in 2050 is provided by the utility company. Simple mitigation methods are tested to improve voltage profiles and complete this case study.

Xie, Jing↗
DOE OSTI2020

Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore

The planning of district-scale electric grids, i.e., distribution grids, has traditionally relied on finding the most cost-effective design such that they are able to supply the peak loads in a district. With the advent of electric demand side flexibility (DSF), there is the opportunity to reshape peak loads such that the investment cost of the electric grid decreases in exchange for a minor increase in the operation cost. This paper formulates an optimal planning approach for the electric grid at the district scale, which incorporates the DSF from thermal building systems, e.g., heating ventilation and air-conditioning (HVAC) systems. The problem is formulated as a mixed-integer linear program (MILP) and aims at minimizing the investment cost for the grid along with the operation cost of the flexible loads. This is subjected to the fixed electricity demand and thermal comfort constraints of building occupants. To this end, linear models for the thermal comfort in the buildings and the power flow in electric grid are considered. The approach is tested on a district planning test case based in Singapore, where the results show up to 30.9 % reductions in investment cost and up to 3.7 % reduction in total annualized cost. Urban planning authorities, developers and utility companies can all benefit from the presented approach to make optimized investment decisions. For building operators, the results point to the need of adopting their control systems for DSF.

Troitzsch, Sebastian↗
DOE OSTI2020

Real-time power management technique for microgrid with flexible boundaries

In order to diminish the impacts brought by high penetration of renewable energy on the reliability of distribution systems, some distribution networks (e.g. Chattanooga electric power board system) have deployed smart switches (SSs) to island some areas to mitigate outage losses. However, due to intermittency and sharply changing rate of renewable energy, it is likely to experience insufficient or excessive power for islanded areas. Therefore, a microgrid controller featured with flexible boundaries is proposed. With proposed microgrid controller, the microgrid can not only shrink or expand its boundaries according to current renewable energy supply, but also disconnect/connect to the main grid with a designated SS. Furthermore, to ensure the microgrid controller could obtain suitable boundaries on the time scale of seconds, a real-time power management technique with alternative generating algorithm is designed to generate all possible alternative boundaries and choose the optimal one, which is scalable to any topology. In addition, in order to maintain state of charge of batteries within a desirable range, anti-overcharge/discharge strategies are designed. Four comprehensive experiments verify that the implementation of the microgrid controllers can realise flexible boundaries and deal with sharply changing rate of renewable generation or load on the time scale of seconds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Forecasting EV Charging Demand on the Distribution System

The U.S. transportation and electricity sectors have historically operated independently, but the growth of electric vehicles (EVs) is driving their convergence. After decades of stagnant demand, utilities must prepare for rising load growth, driven in part by transportation electrification. Utilities must anticipate when and where these new loads will materialize to effectively manage EV growth and maintain grid reliability. This presentation outlines NREL's approach to developing high-resolution EV load datasets for distribution planning, with insights from the Multi-State Transportation Electrification Impact Study on EV and load forecasting, infrastructure requirements, and managed charging strategies.

25 ENERGY STORAGE↗
DOE OSTI2022

Performance Evaluation of Distributed Energy Resource Management Systems Using Software- and Hardware-in-the-Loop

Distributed energy resource management systems (DERMS) are an important emerging technology for coordinating distributed energy resources (DERs) integrated in power distribution networks. These solutions implement a software platform to monitor, control, and coordinate DERs in real time to provide aggregate grid services to the electric utility or distribution system operator. To move DERMS technology forward, research and performance validation in a laboratory environment are needed to ensure proper function of DERMS prior to field deployment. This presentation presents a generic hardware-in-the-loop (HIL) platform to evaluate performance of DERMS using software-in-the-loop (SIL) and power HIL. The platform provides realistic testing in a laboratory environment, including accurate modeling of full-scale distribution systems, DERMS software controllers, and at-power distributed energy resources (DERs), such as solar and battery inverters. Two case studies are presented to demonstrate how the platform can be used independently as an integrated development and validation approach for different projects. Laboratory testing results are included to showcase the voltage regulation performance of each study and the benefits of implementing such a platform for DERMS evaluation.

DERMS↗
DOE OSTI2023

Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations

This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers' privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.001% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Improved Line Outage Detection in Transmission Systems with Few PMUs

Unlike transmission systems, distribution systems historically lack enough measurements, making their real-time monitoring almost impossible. Recent deployment of diverse types of devices such as phasor measurement units (PMUs), smart meters, solar inverters and weather information sensors opens up new ways of monitoring these systems, with the assistance of customized machine learning (ML) applications. The paper describes a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams and creates synchronous measurement snapshots to be used by a hybrid robust state estimator (SE) which provides not only accurate state estimates but also real-time feedback for ML model refinement. Improved monitoring performance due to the use of developed computational framework is experimentally observed by simulated scenarios on an electric utility’s distribution system.

Distribution systems, graph learning, machine lear↗