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DOE OSTI2023

Implications of Battery Storage for Solar Net-Metering Reforms

Compensation structures for residential solar PV are evolving toward a model that incentivizes the use of battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner often provide no grid value, due to misalignment with market prices. Incentivizing customers to discharge storage in response to market prices, particularly on infrequent peak load days would greatly enhance storage dispatch value. However, doing so requires consideration of local distribution network impacts. We illustrate a net billing design that yields a storage dispatch value equal to 50-70% of its maximum potential market value, without materially degrading solar self-consumption levels or increasing local grid stress.

Barbose, Galen↗

DOE OSTI2022

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗

DOE OSTI2022

Optimal Energy Storage System and Smart Switch Placement in Dynamic Microgrids With Applications to Marine Energy Integration

Here this paper studies a dynamic microgrid (DMG) planning problem that places energy storage systems (ESSs) and smart switches (SSWs) optimally in the system. We apply the proposed methodology to applications concerning marine renewable energy (MRE). MRE is an emerging clean energy resource with enormous capacity but volatile and intermittent energy output profiles. Innovative grid-integration technologies designed to enhance the reliability of an MRE-integrated system are needed. However, there are still limited studies in this regard. Existing works have shown the promising prospect of using a dynamic microgrid (DMG) operational concept to accommodate renewable resources in distribution systems, but they usually assume fixed ESS and SSW installations. To further improve the operational flexibility of DMGs, we propose a DMG planning methodology that optimally places ESSs and SSWs so that a DMG with MRE is warranted with proper resource adequacy and topological flexibility in both the contingency and normal operations. We use realistic case studies based on a real-world distribution network and the U.S. Department of Energy's MRE dataset to verify the value and validity of the proposed work.

25 ENERGY STORAGE↗

DOE OSTI2013

Improvements realized on the cryogenic solution called NiThrow{sub TM}

The economic, environmental, social and societal constraints have pushed the nuclear industry to develop new dismantling and decommissioning (D and D) techniques in order to meet the current industrial requirements. Since 5 years, AREVA, in partnership with Air Liquide, has been working on a new cryogenic solution that can be used to achieve the main important D and D operations (i.e. cutting, surface decontamination and concrete scrabbling). This solution, called NiThrow{sup TM}, is based on the Nitrocision LLC concept and consists in spraying highly pressurized liquid nitrogen (3500 bar) at a very low temperature (-140 deg. C) onto a surface. The main advantage in using liquid nitrogen instead of water is due to its rapid conversion into gaseous nitrogen that will avoid the generation of liquid effluent. The preliminary trials made in France at Saint Ouen l'Aumone and at the AREVA SICN facility by using NiThrow{sup TM} appeared to be very interesting and promising in terms of effectiveness, reduction of the dosimetry (i.e. ALARA principle) and adaptability to the different types of surfaces and materials to be treated. On an other hand, they also highlighted a couple of defects like a lack of reliability that is not compatible with a safety use in a nuclear environment. In 2009, with the aim of fixing all these issues, AREVA decided to start an extensive R and D program. This work has been essentially focused on the lancing tool, the insulation and the flexibility of the liquid nitrogen distribution network, but also on the design and the manufacturing of a waste collection unit and a dedicated carrier. Today, these R and D efforts have been totally completed. and resulted to the publication of 3 patents. Also, the collaboration, with Air Liquide and the American company Conco allows AREVA to propose to its customers a safe and reliable solution for their cleaning operations in France and all over the world. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Study of self-assembly behavior and ionic conductivity of conjugated liquid crystals with T-shaped facial-polyphilic structure

The unique self-assembly of liquid crystals (LCs), combined with their potential application as organic semiconductors, has become a focus of recent research. Here, a joint experimental and computational study of the self-assembly and ionic conduction was carried out on a series of T-shaped conjugated LCs consisting of three incompatible components. By extending the EOn side-chain length, several experimental evaluations confirmed a decrease of the order-disorder transition temperature, while coarse-grained simulations revealed a structural evolution from a smectic phase to a columnar phase. Ionic conductivity of these molecules was achieved by adding Li salt, leading to a maximum conductivity of 1.1 × 10 −3 siemens per centimeter observed at 120°C. All-atom simulations were performed to examine the Li-ion solvation environment and to evaluate the intrachain and interchain Li-ion hopping mechanisms. The molecule with a long EOn side chain was found to generate a densely distributed network of Li-ion solvation sites, which can facilitate effective interchain hopping to promote ion transport.

Liu, Ziwei [Cornell Univ., Ithaca, NY (United Stat↗

DOE OSTI2018

Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]

Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers’ benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.

Dall-Anese, Emiliano↗

DOE OSTI2020

WaterModelsAnalytics.jl

WaterModelsAnalytics.jl is an analytics package for visualizing water distribution networks in Julia.

Stickel, Jonathan↗

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 OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗

DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗

DOE OSTI2024

FIREWHEEL

SAND2024-16910O FIREWHEEL is a tool for experiment orchestration that assists a user in building and controlling repeatable experiments of distributed network systems at any scale. This version also includes FIREWHEEL v2.7 and its associated companion model components. With FIREWHEEL, users can easily construct modular parts of a cyber system, called Model Components. The Model Components can be combined to form an experiment. Most experiments are then instantiated using an emulation tool, such as minimega.

Kajder, Thomas↗

DOE OSTI2017

Structural Evaluation of Complex Subcomponents Manufactured by Large Scale Extrusion Deposition of Carbon Fiber Reinforced ABS

The large scale extrusion deposition process has recently been commercialized in the form of additive manufacturing machines such as the BAAM from Cincinnati Inc., which enables layered production of chopped fiber reinforced thermoplastic polymer systems. The application of this process to the automotive market is being pursued by Local Motors to enable rapid design to market cycles and build on-demand capability for a wide range of vehicle styles from a distributed network of micro-factories. This endeavor will require an understanding of the structural performance of components with complex geometries, where the properties are known to vary as a function of printing conditions, as well as orientation and shape. In order to rapidly build a database of structural performance, a beam specimen with outer dimensions of 914 x 305 x 64 mm3 was selected to be subjected to bending, torsion, and shear loading with full field displacement measurement by digital image correlation (DIC). A total of 25 different specimen configurations were designed including variation of print geometry, reinforcement by foam filling, and overwrapping with advanced composites. This work documents the results of the study and presents the relative performance of the structures in addition to the approach to simulation that is being initiated to serve as a framework for efficient design of structures manufactured in this way. The results are presented as a table of structural efficiency including stiffness and strength as functions of mass for each design. Additional results will also be provided in the form of surface displacements from DIC; future work will utilize this data to better optimize simulations for predicting structural performance of articles manufactured by this process.

Bedsole, Robert↗

DOE OSTI2014

Recovery Act: Geothermal Data Aggregation: Submission of Information into the National Geothermal Data System, (Final Report, June 24, 2014)

The National Geothermal Data System (NGDS) is a Department of Energy funded effort to create a single cataloged source for a variety of geothermal information through a distributed network of databases made available via web services. The NGDS will help identify regions suitable for potential development and further scientific data collection and analysis of geothermal resources as a source for clean, renewable energy.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

Smart Grid Enabled EVSE

The combined team of GE Global Research, Federal Express, National Renewable Energy Laboratory, and Consolidated Edison has successfully achieved the established goals contained within the Department of Energy’s Smart Grid Capable Electric Vehicle Supply Equipment funding opportunity. The final program product, shown charging two vehicles in Figure 1, reduces by nearly 50% the total installed system cost of the electric vehicle supply equipment (EVSE) as well as enabling a host of new Smart Grid enabled features. These include bi-directional communications, load control, utility message exchange and transaction management information. Using the new charging system, Utilities or energy service providers will now be able to monitor transportation related electrical loads on their distribution networks, send load control commands or preferences to individual systems, and then see measured responses. Installation owners will be able to authorize usage of the stations, monitor operations, and optimally control their electricity consumption. These features and cost reductions have been developed through a total system design solution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Development of ultra-high field superconducting magnetic energy storage (SMES) for use in the ARPA-E project titled “Superconducting Magnet Energy Storage System with Direct Power Electronics Interface”

The purpose of the CRADA is to enable superconducting magnetic energy storage (SMES) for grid-level applications by developing a cost competitive, high energy-storage density, ultra-high field SMES coil using 2G HTS wire in combination with a flexible new modular power electronics interface capable of connection to medium voltage distribution networks.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAIC) Atmosphere Science Plan

Arctic climate change is amplified relative to global change, and is embodied by a dramatic decline in the perennial sea-ice pack. These cryospheric transitions carry significant implications for regional resource development, geopolitics, and global climate patterns. Indeed, the changing arctic cryosphere is considered a grand challenge for global climate research. Arctic change, and its linkages with the global system, must be understood. Additionally, there is a growing stakeholder community that requires improved sea-ice forecasting for many applications. To make progress on these important issues requires developing a detailed, process-level understanding of the coupled climate system that can help to address the numerous deficiencies in numerical model representations of the Arctic. Such an understanding is only possible by making targeted, interdisciplinary measurements within the central arctic sea-ice environment. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) initiative has been developed in response to these great challenges. It comprises three parts: 1) An intensive, icebreaker-based observatory that will freeze in, and drift with, the arctic sea ice for a full annual cycle making interdisciplinary measurements in the atmosphere, sea ice, upper ocean, and biosphere; 2) A distributed network of targeted, autonomous measurements to characterize spatial variability on model grid-box scales; and 3) Coordinated, multiscale analysis and modeling activities. MOSAiC is a major, international effort that will involve participation of many different agencies and entities. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is uniquely positioned to play a critical role in this initiative by providing a comprehensive instrument suite to characterize the atmosphere and its interactions with the sea-ice surface. ARM will deploy its second Mobile Facility (AMF2) and Mobile Aerosol Observing System (MAOS) at the MOSAiC central observatory as it drifts through the central Arctic for a 13-month campaign starting in September 2019. Sea-ice is an integrator of energy fluxes in the coupled arctic climate system; thus, atmosphere-ice-ocean processes impacting the flow of energy through this system in all seasons are the primary target of MOSAiC. The broader, collaborative MOSAiC initiative will allow for many interdisciplinary studies along this theme. ARM’s involvement will target specific areas related to the atmosphere and atmosphere-surface interactions that are critically under-observed in the Arctic, are leading contributors to model uncertainties in the region, and are programmatically important to DOE research and modeling programs. The guiding science themes for this project include: (1) The surface energy budget of sea ice; (2) Clouds and precipitation; (3) Aerosols; and (4) The atmospheric boundary layer. Many fundamental issues concerning these themes are lacking in observational constraints, particularly in the arctic winter and through consecutive seasons. For example, little is known about the energy budget of first-year sea ice, the annual cycle of central arctic aerosol concentrations, the spatial organization of cloud-precipitation systems relative to sea-ice heterogeneity, the winter boundary-layer evolution, or cloud-surface coupling processes over sea ice. The proposed ARM observations will be groundbreaking in many ways, and will ultimately have a dramatic impact on the arctic research community and its ability to represent coupled arctic processes in numerical models.

North Slope of alaska, Arctic sea ice, Barrow, Arc↗

DOE OSTI2018

Fibre Channel Development Final Report CRADA No. TC-0340-92-C

The Fibre Channel (FC) Development project was designed to enhance U.S. industrial competitiveness by accelerating the standardization and subsequent industrial acceptance of the American National Standards Institute’s (ANSI) Fibre Channel Standard (now X3T1 1). It was also intended to give the principal U.S. participants a one-to two-year lead in developing heterogeneous high-speed computer networks, distributed computing through clustering, scientific visualization techniques, and high speed channels. The project was proposed to benefit U.S. industry as these high performance computing methods became generally available. In 1992-93, during the initial project phases, Fibre Channel (FC) was emerging as a new ANSI standard. It was envisioned as becoming the mechanism for data transfer between the next generation of computers, and between these computers and their peripherals. Using this channel standard, U.S. computer vendors were expecting to be able to provide high-speed interoperatillity between heterogeneous computers and their storage devices, with data transfer rates greater than a GBit/sec. Our project was composed of key principal players in the FC standardization effort from both U.S. industry and the Department of Energy’s@OEs) Lawrence Liverrnore National Laboratory (LLNL). The industrial participants were developing individual FC interfaces to operate with their platform products. LLNL’s.role was to be a neutral testing site and a facilitator for helping to resolve conflicting interpretations of the embryonic Fibre Channel specification. LLNL anticipated that conflicts in the interpretation of such a standard would arise and require neutral resolution and that such resolutions would best be achieved in cooperation with the ANSI FC Working Group. Project plans included transferring to U.S. industry any resilient FC testing capabilities at the project conclusion.

42 ENGINEERING↗

DOE OSTI2019

Classification of Methane Emissions from Industrial Meters, Vintage vs Modern Plastic Pipe, and Plastic-lined Steel and Cast-Iron Pipe (Final Report)

The project focus was to improve the characterization of methane (CH 4 ) emissions currently detailed in the U.S. Environmental Protection Agency (EPA) Greenhouse Gas Inventory (GHGI) for categories of assets within the Natural Gas (NG) distribution system to isolate what is driving inflation or deflation behind current, nationwide, aggregated Emission Factors (EFs). These specific categories included industrial/commercial NG customer meters, modern and vintage plastic pipe, along with plastic-lined steel and cast-iron pipe. CH 4 emission rate data was gathered during 25 sampling campaigns at industrial/commercial meter sites, vintage and modern plastic pipe sites, as well as plastic-lined steel and cast-iron sites located within NG distribution networks.

03 NATURAL GAS↗