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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services

This paper develops a hierarchical control frame-work to aggregate and to manage behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. In the proposed framework, firstly, each controller in the hierarchy determines the flexibility of the DERs such that the obtained flexibility is feasible with respect to its operational purview. For example, the operational purview of a home energy management system may only consider consumer comfort preferences, while that for an aggregator or a grid controller may consider network voltage management as well. Based on the feasible flexibility, optimal setpoints for the DERs is then determined by the hierarchical controllers to help the distribution power network in voltage regulation, coordination issues with existing transmission-level conventional generators, etc. Therefore, the proposed strategy, which is based on model-predictive control, can be effectively utilized by the distribution network to coordinate several DERs to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Demand Response in Residential Energy Code: Technical Brief

As buildings account for over 75% of U.S. electricity use, effectively managing their loads can greatly facilitate the transition towards a clean, reliable grid. Grid-interactive efficient buildings (GEBs) combine efficiency and demand flexibility with smart technologies and communication to provide occupant comfort and productivity while serving the grid as a distributed energy resource (DER). In turn, GEBs can play a key role in ensuring access to an affordable, reliable, sustainable, and modern U.S. electric power system. Their national adoption could provide $\$$100-200 billion in U.S. electric power system cost savings over the next two decades. The associated reduction in CO 2 emissions is estimated at 6% per year by 2030 (DOE 2021). Building codes represent standard design practice in the construction industry and continually evolve to include advanced technologies and innovative practices. Historically, national model energy codes establish minimum efficiency requirements for new construction (ICC 2020). Expanding codes to support GEB capabilities is a pivotal step towards realizing demand flexibility in support of a clean grid by addressing capabilities to improve interoperability between smart building systems, the grid, and renewable energy resources. Realizing GEBs requires buildings with automated demand response (DR) capabilities that enable standardized communication with or control of, subject to explicit consumer consent, energy smart appliances or home energy management systems. This is achieved through direct or indirect (i.e., via an aggregator) communication between appliances and the electric grid. Energy codes can also support DR communication standardization and advance the deployment of building-integrated DERs such as energy storage, generation, and electric vehicles (EVs). Incorporating automated DR capabilities in energy codes provides many benefits to the consumers. Specifically, it aligns building electric load demand with intermittent renewable energy source availability, decreases peak load on the electric grid, allows buildings to respond to utility price signals, supports electrical network reliability and market growth of products and processes aligned with clean economic growth. The incorporation of DR into the model residential energy codes was considered for both the 2021 and 2024 International Energy Conservation Code (IECC) code development cycles. The approved DR measures in the 2021 cycle were removed in response to appeals (ICC 2020). Updated language was presented for consideration again for the 2024 IECC, where it was negotiated and again approved, and again removed in response to appeals (ICC 2024). This resulted in many sections, including sections on demand responsive controls, being moved to the credits options or an appendix as a voluntary application. This technical brief updates the proposed DR components such that they can be considered by states and local governments for direct incorporation into their codes, as well as for future IECC energy code development. The proposal refinements are intended to support consistency in approach and provide a degree of certainty for building owners, designers, contractors, manufacturers, and building and fire safety professionals. The scope of this technical brief includes three strategies for DR in residential buildings: 1) smart thermostats with demand-responsive control, 2) electric water heating incorporating demand-responsive controls and communication and 3) grid Integrated solar and energy storage systems.

2021 IECC↗
DOE OSTI2023

Skewering the silos: using Brick to enable portable analytics, modeling and controls in buildings

Nearly all large commercial buildings have heating, ventilation and air conditioning (HVAC) systems, lighting systems, safety and other systems controlled by a computer—a dedicated server with a building energy management system (BMS). However, these BMSs are proprietary with each building’s assets (that is, fans, valves, pumps, and their setpoints) named and coded uniquely by the BMS vendor or engineer; building analytics and control algorithms are written specific to the assets and the building. Thus, any control updates or analytics to improve building performance—especially critical to reduce greenhouse emissions or improve load flexibility—are labor intensive and costly. The Brick schema was developed so the same analysis or control algorithms can work on a variety of buildings if each is digitally represented in a Brick data model. The goal of this project was to further the development of Brick to extend it beyond an academic project with demonstrated success in a small field study, to a practical choice for industrial and commercial stakeholders seeking to realize value from building data. To do this, we executed four objectives: (1) expand the Brick schema including its modeling capabilities and vocabulary, (2) develop tools for integrating Brick with existing digital technologies and representations in buildings, (3) develop an open-source analytics platform to facilitate use of Brick in delivering data value, and (4) demonstrate Brick-driven analytics and controls in real settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach

The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Controller Hardware-in-the-Loop Modeling and Operation of a High-Power DC Charging Hub

High-power charging (HPC) concept will be a critical enabler for the wide-scale adoption and integration of electric vehicles (EVs). HPC hubs will have a significant impact on achieving this goal, particularly when considering the charging requirements of next-generation medium and heavy-duty vehicles (MD/HD) used in various vocational scenarios. This emphasizes the significance of evaluating and confirming the technical planning and multi-level operation of HPC hubs through modeling, protocol implementation, and simulation before hardware demonstration. The focus of this study is to develop the architecture, modeling, communication, and real-time controller hardware-in-the-loop (C-HIL) simulation of HPC hubs using the DC distribution system approach. Specifically, this work demonstrates the practical implementation of a custom Smart Energy Management System (SEMS) for a real-time C-HIL HPC hub simulation using the Open Charge Point Protocol (OCPP) for communication. OCPP is implemented on the Node-Red framework and the custom controller is executed in Python. We developed a rule-based controller to demonstrate the proposed approach.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

MPC-based double-layer real-time conditional cSelf-restoration for interconnected microgrids

In this report, we propose a novel model predictive control(MPC)-based real-time conditional self-restoration energy management system (CSR-EMS) for interconnected microgrids (IMGs) integrated with renewable energy sources (RESs) and energy storage systems (ESSs). Superior to the existing IMG self-restoration methods, the “conditionality” of the proposed CSR-EMS can economically realize self-restoration and grid-assisted restoration during energy deficiency or faults, in both islanded and grid-connected modes. Cost minimization is implemented as the objective function to judge in real-time which restoration mode is economically preferred. The proposed CSR-EMS comprises two layers–the lower layer operates locally to eliminate electricity fluctuations created by RESs and ensure economic effectiveness within an MG, whereas the upper layer oversees the real-time operational status of the IMG system and determines power exchange among microgrids (MGs) during abnormalities. In detail, when a microgrid inside the IMG system experiences an energy deficiency, the CSR-EMS, on an MPC basis, intelligently optimizes power production from each dispatchable distributed generator (DG), ESS, power imported from the main grid, and power exchange among the IMGs to maintain the demand–supply balance, while considering system recovery cost, state of charge (SoC) of ESSs and operation modes of the IMGs (i.e., grid-connected or islanded mode). Simulation results and comparisons with existing IMG self-healing EMSs demonstrate the economic efficacy of the proposed CSR-EMS strategy during normal and abnormal operations, which can be used as an energy control framework for modern power systems with multiple interconnected microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Modelling of Wastewater Heat Recovery Heat Pump Systems

Wastewater heat recovery is currently an underutilized technology that could be part of solving the climate crisis. A large portion of the heat that leaves a building in the form of wastewater is potentially recoverable for pre-heating domestic hot water or other service water systems. While there are several different approaches to wastewater heat recovery, this project focused on creating detailed, integrated building models for wastewater heat recovery heat pump systems. EnergyPlus models were developed featuring inputs and assumptions corresponding to manufacturers’ specifications, performance lab test data and feedback from engineering consultants. EnergyPlus’s supervisory control Energy Management System objects were heavily relied upon to overcome modelling challenges. The developed EnergyPlus model was integrated into U.S. Department of Energy New Construction Reference Building models for various climate zones and building types to assess potential energy use, energy cost and greenhouse gas emission reductions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A Power Application Developer’s Guide to the Common Information Model: An Introduction for Power Systems Engineers and Application Developers – CIM17v40

A key issue in creating the next generation of energy management system (EMS) and advanced distribution management system (ADMS) platforms will be the ability to represent and exchange power system network model data in a consistent manner. To this end, the Common Information Model (CIM) stands out as the only standardized vocabulary (or ontology) for defining power system network models and asset data in a comprehensive, consistent manner across the generation-transmission-distribution boundary. The CIM is freely available to use and extend. The CIM is maintained by the UCAiug (informally known as the CIM User’s Group) under an Apache 2.0 license. The CIM Users Group collaborates with the IEC and other standards communities for the development of technical and informative specifications. Although portions of the information model are referred to by the corresponding IEC standards naming, it is not necessary to purchase any of the IEC standards to use the CIM information model. This document provides a roadmap for power system engineers and application developers not familiar with semantic modeling to start using the CIM for modeling, simulation, optimization, and development of advanced power applications. The key classes needed for defining power system topology and equipment are explained systematically. Key focus areas include modeling of lines, transformers, generators, switching equipment, loads, and distributed energy resources (DERs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meetings: High Power Charging (HPC) Summary Report

Electric vehicle (EV) adoption will change the composition of EV charging load to higher-power charging as more medium- (MD) and heavy-duty (HD) applications are electrified, and as all vocations, including light-duty (LD) vehicles, are capable of faster charging. These shifts provide the opportunity for high-power charging (HPC) and facility equipment to evolve and improve efficiency, cost, and space. High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project designs and develops a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration approaches and technology solutions. The project addresses (1) interconnection and management of a grid-tied inverter; (2) development of a DC distribution system that is responsible for system energy management, interoperability, and DC protection; (3) modular DC/DC conversion for vehicle charging; (4) EV charging interface and DC/DC integration; and (5) smart charge control and vehicle-to-edge (vehicle-to-building [V2B], vehicle-to-everything [V2X]) capability. This summary presentation is the first technical progress output of the project. It provides insight for the first deep-dive technical meeting outputs in terms of research presentations and also includes summary of the discussions occurred in the follow-up breakout sessions. The summary presentation covers three technical areas: (1) HPC: State of the art power architectures and the design of the power electronics, (2) Modeling, energy management, and power control in the HPC station, and (3) Codes and standards work that are in line with the previous two topic areas.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2024

Federated Machine Learning-Based Anomaly Detection System for Synchrophasor Network Using Heterogeneous Data Sets: Preprint

Synchrophasor technology is widely deployed in the energy management system to monitor the grid health at micro level and perform necessary corrective actions in real time; however, integrated phasor devices and data aggregators are exposed to several cybersecurity threats. This paper proposes a federated ML(FML)-based ADS to detect several data integrity attacks in the synchrophasor network. The proposed approach integrates the horizontal FML technique and consists of substation-based local models and a control center-based global model. The proposed methodology includes training local models using heterogeneous data sets that include network and grid information and updating the global model through multiple iterations by sharing model gradients. Finally, the trained global model is applied to identify cyberattacks, normal operation, and physical events. To validate the proof of concept, we used synthetic data sets generated by Mississippi State University and Oak Ridge National Laboratory for training and testing the classification models using the National Renewable Energy Laboratory's high performance computing resources. Our experimental results, computed through several performance measures, reveal that the proposed approach shows consistent performance during the binary, three-class, and multiclass classifications while ensuring privacy of synchrophasor data.

anomaly detection system↗
DOE OSTI2023

Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meetings: High Power Charging (HPC) Summary Report

Electric vehicle (EV) adoption will change the composition of EV charging load to higher-power charging as more medium- (MD) and heavy-duty (HD) applications are electrified, and as all vocations, including light-duty (LD) vehicles, are capable of faster charging. These shifts provide the opportunity for high-power charging (HPC) and facility equipment to evolve and improve efficiency, cost, and space. High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project designs and develops a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration approaches and technology solutions. The project addresses (1) interconnection and management of a grid-tied inverter; (2) development of a DC distribution system that is responsible for system energy management, interoperability, and DC protection; (3) modular DC/DC conversion for vehicle charging; (4) EV charging interface and DC/DC integration; and (5) smart charge control and vehicle-to-edge (vehicle-to-building [V2B], vehicle-to-everything [V2X]) capability. This summary presentation is the first technical progress output of the project. It provides insight for the first deep-dive technical meeting outputs in terms of research presentations and also includes summary of the discussions occurred in the follow-up breakout sessions. The summary presentation covers three technical areas: (1) HPC: State of the art power architectures and the design of the power electronics, (2) Modeling, energy management, and power control in the HPC station, and (3) Next Generation Profiles for high power charging characterization.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Development of a DC Distribution Testbed for High-Power EV Charging

This paper explores the design and implementation of a power hardware-in-the-loop (P-HIL) setup for DC distribution infrastructure integrated with high-power charging (HPC) of electric vehicles (EVs), DC loads, and sources. The utilization of DC distribution holds significant potential for enhancing the operation of a HPC station architecture. However, there are challenges establishing a DC charging hub including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and lack of common system level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products to evaluate different use cases at rated power and voltage levels. The developed P-HIL setup features a dedicated DC charging hub, DC-coupled chargers, DC loads/sources, DC protection, and a communication architecture. The integrated P-HIL system provides a versatile testing environment to address technology and interoperability gaps and implements a smart energy management system (SEMS). This platform enables comprehensive and robust testing of COTS devices, charger prototypes, SEMS controllers and protection schemes, which together will accelerate transition to EVs at scale. The setup is tested for various use-cases at full-scale, integrating 950 V DC bus voltage, 660 kW grid-tied inverter, 150 kW COTS charger, and 100 kW energy storage system within an open-source SEMS platform.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2023

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗
DOE OSTI2024

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗
DOE OSTI2024

OT Operational Anomaly Detection (OAD) T&D + DER

The growth of utility-scale renewable energy resources, distributed energy resources (DER), and transportation electrification has increased uncertainty and cybersecurity risks in power grids. The Purdue Enterprise Reference Architecture model which is widely adopted by the utility industry is now insufficient to protect the power grid against cyber-attacks. There is a need to identify what cybersecurity model is effective on Energy Management System (EMS), Advanced Distribution Management System (ADMS), and DER Management System (DERMS) to address the fundamental cybersecurity challenges in the age of increasing renewable energy and DER share as well as consumer participation in the electric energy industry. The next generation of cybersecurity model for OT network should be able to detect inside attackers, mitigate the cybersecurity risks arising from the new grid participants including DER aggregators, electric vehicle owners, and behind-the-meter consumers outside the utility company, and develop the strategy to trust consumer measurement data. This panel will discuss the challenges and pathways for the development of an ensemble cybersecurity model based on predictive state estimation to detect cybersecurity anomalies in OT network including EMS, ADMS, and DERMS.

cybersecurity↗
DOE OSTI2020

AURORA - AUtonomous and Resilient Operation of energy systems with RenewAbles

This presentation provides an overview of the AURORA project. The objective of AURORA is to develop and validate novel functions for Energy Management Systems (EMS) containing Security Situational Awareness (SSA), Distributed Microgrid Coordination (DMC), Autonomous Microgrid Restoration (AMR).

14 SOLAR ENERGY↗
DOE OSTI2025

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Energy Efficiency as a Foundational Technology Pillar for Industrial Decarbonization

The U.S. government aims to achieve net-zero greenhouse gas emissions by 2050 to reduce the severe impacts of climate change. The U.S. industrial sector will become a focal point for decarbonization since it accounts for 33% of the nation’s primary energy use and 30% of its energy-related CO2 emissions. Industrial emissions are also expected to increase by 15% through 2050, making the industrial sector a logical target for decarbonization efforts. Energy efficiency technology pathways provide low-cost, foundational routes to decarbonization that can be implemented immediately. Energy efficiency technology pathways, such as strategic energy management, system efficiency, smart manufacturing, material efficiency, and combined heat and power, are well established and would immediately reduce energy use and emissions. However, their role in the aggressive net-zero decarbonization pathway for the industrial sector is still unclear. This study aims to address energy efficiency pathways for decarbonization, and reviews studies related to these technologies for industrial decarbonization through 2050. This study identifies different strategies for the industrial sector in general and that are specific to six energy-intensive industries: iron and steel; chemical; food and beverage; petroleum refining; pulp and paper; and cement. Finally, a path toward the successful implementation of energy efficiency technologies is outlined.

Strategic energy management↗