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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices: Preprint

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗
DOE OSTI2020

Integrating System to Edge-of-Network Architecture and Management for SHINES (SEAMS) Technologies of High Penetration Grids

Consistent with the U.S. DOE’s EERE SHINES FOA objectives, the goal of this project was to enable integration from EMS to variable DER in a way that delivered visibility and opportunities for managing and controlling distributed resources using SEAMS technologies. This project implemented several SHINES technologies, which included: (1) three Stem battery systems; (2) six ConnectDER PV collars; (3) two E-Gear PV/Battery storage interfaces; and (4) eight Kitu smart inverter emulators. A Siemens Energy IP DEMS was deployed in a development environment and integrated with the SHINES technologies via OpenADR and IEEE 2030.5 protocols with documented architecture. In the case of IEEE 2030.5, a suite of technologies including a gateway, an API, software and a server from Kitu Systems (the Citadel, Convoy, Kitu Crosslink API, and Kitu Spark) were used to demonstrate that the utility could achieve visibility of distributed energy resources (DER) and control of single and multiple DER systems with a single command. The project also included a LCOE analysis of SHINES technologies compared to traditional system and circuit mitigation measures.

14 SOLAR ENERGY↗
DOE OSTI2022

Towards Optimal and Executable Distribution Grid Restoration Planning With a Fine-Grained Power-Communication Interdependency Model

Distribution service restoration (DSR) under natural disasters is always a critical and challenging problem for utility companies. An effective solution must not ignore the power-communication interdependency as various systems are getting increasingly connected in the Smart Grid era. In this paper, we propose a two-layer distribution system model with both power and communication components. Based on this model, we formulate the restoration process as a routing problem that schedules the path and action sequence of utility crews that involves repairing damaged components, closing power switches, and enabling communication paths between the control center and remote field devices. Further, we develop a simulation-based method to quantitatively evaluate the restoration process with public reference models of large-scale power systems. The experimental results show that our method improves the total restored energy up to 57.6% and reduces the recovery time up to 63% by considering the power-communication interdependency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters: Preprint

Smart inverters (SI) have huge potential in providing grid services which has not been fully realized yet. One of these grid services, distribution network voltage regulation by SI, can improve the network voltage by regulating the SI reactive and active power output. Voltage regulation by SI is much faster compared to traditional voltage regulating devices, e.g. tap changing transformer, capacitor banks. However, there is gap in available published literature on the characteristics of SIs when the SI is controlled by local controller or external control signal. This paper presents the experimental study to characterize SI reactive power regulation response to two different control methods: autonomous control method and remote dispatch method. It was found that IS reactive power regulation response could be significantly different in terms of delay, and ramp rate for these two methods. Finally, Power-Hardware-in-The-Loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL tests results show that SI response characteristics for autonomous control method and remote dispatch method need to be considered during planning for distribution network voltage regulation using SI.

autonomous control↗
DOE OSTI2023

Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids

With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.

digital real-time simulation↗
DOE OSTI2024

Field Demonstration of Residential DER Service-Oriented Load Participation

Amidst a concerning surge in power consumption during peak hours, coupled with heightened power grid instability, and driven by a growing demand for electricity, aggregations of Distributed Energy Resource are becoming a viable means for providing essential reliability services.Electric utility companies have proactively implemented Demand Response programs for decades. These programs employ Direct Load Control methods to enhance power grid stability, achieved by controlling customers’ Distributed Energy Resource during peak hours to reduce power consumption. However, a notable drawback of Direct Load Control has been high unenrollment rates of DR program participants due to customer discomfort.Therefore, the underlying issue of over-consumption persists. To address these concerns, this paper introduces a Service-Oriented Load Participation approach to providing grid services such as Demand Response. Leveraging a Service-Oriented Architecture, this method offers the advantage of efficient service management and provisioning within the system. The SOLP approach not only aims to reduce power consumption but also to maintain customer satisfaction by ensuring a comfortable grid service experience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

EVs-at-RISC: A Secure and Resilient Interoperable SCM Control System Architecture for Electric Vehicle’s-at-Scale (Final Technical Report)

The EVs-at-RISC project was a five-year research, development, and demonstration initiative to create foundational tools for utility-scale fleet aggregation and Smart Charge Management (SCM) of Electric Vehicles (EV), Electric Vehicle Charging Infrastructure (EVCI), and related Distributed Energy Resources (DER). Rather than seeking to develop and demonstrate highly perfected SCM algorithms and control strategies, this project instead focused on creating foundational software solutions that enable unprecedented digital interoperability across the communications technologies and vendor platforms used to manage EV , EVCI, and DER, as well as existing energy management infrastructure operated by utilities, grid operators, and aggregators. This project then extends these novel interoperability capabilities to develop and deploy powerful middleware abstractions across grid edge networks and EVCI/DER fleet aggregations incorporating modern software tools and best practices, such as CI/CD, to bring the immense capabilities of infrastructure-as-code and policy-as-code to modern grid edge network environments. This addresses the foremost systemic issues preventing realization of any net operational benefits from scaled deployment of behind-the-meter EV, EVCI, and DER assets in electric power grids and markets today. The results of this approach and project unlock massive potential for new SCM capabilities to be easily prototyped, evaluated, and deployed at-scale within the existing grid edge network infrastructure and EVCI/DER technology ecosystem. The EVs-at-RISC project achieves this by extending Open Field Message Bus (OpenFMB), a conceptual model for digital interoperability and distributed intelligence in traditional front-of-meter utility SCADA networks, validating our hypothesis that OpenFMB could be similarly used to solve systemic digital interoperability issues in behind-the-meter environments and unlock real-world utility-scale SCM capabilities without requiring any new proprietary vendor solutions or significant infrastructure reconfiguration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗
DOE OSTI2021

Systems and methods for advanced grid integration of distributed generators and energy resources

A circuit for a smart photovoltaic (PV) inverter system and the smart PV inverter system are described. The circuit includes one or more strings coupled to an electrical load. Each of the one or more strings further includes one or more string members coupled in series, where each of the one or more string members comprises a voltage source and an inverter. The circuit also includes a controller to receive an output from an operator controller and control the strings, where the controller is configured to control the strings by providing a function command to a first string member of each of the one or more strings based on the output from the operator controller. The voltage source may also receive an output from an energy output device. Further, the inverter may be configured to convert the output of energy output device into an energy source of electrical load.

Bhowmik, Shibashis↗
DOE OSTI2023

Using Synchronization as an Indicator of Controllability in a Fleet of Water Heaters

Peak reduction is an important concern that can help reduce the growing stress on distribution grid and allow to defer investments in new capacity. However, the growing concern for customer privacy and comfort may impact the performance of load control for residential devices. Water heaters represent a convenient way of reducing peak due to their ability to store thermal energy for future use. In this paper, we developed a methodology to help utilities gain more insight with respect to the impact of load control efforts for shaving peak with no necessary information about the water heaters except the device status (on/off). To this end, we use a fleet of water heaters in a controlled residential neighborhood in Atlanta, GA. Our findings show that convergence in device status can serve as a proxy for peak shifting during hours of the evening peak.

demand response↗
DOE OSTI2026

V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale

Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.

Manne, Nithin↗
DOE OSTI2021

Application of Site Controllers for Electrification of Commercial Fleet Vehicles

Electrification of transportation fleets presents a significant challenge for commercial customers. These challenges can be specific to region, weather, operating schedule, charging infrastructure, and other factors. This paper presents the value of integrating a site controller to monitor the health of assets and co-optimize the operation of commercial sites with multiple distributed energy resource technologies and electric vehicle fleets. The tests demonstrate smart-charging and vehicle-to-building uses compared to business-as-usual cases. The secondary objectives of power management for the customer vehicle are optimized by a planning tool (REopt) and integrated using the site controller. Any deviations from the planned dispatch are addressed by the real-time controllers offering tertiary controls, such as energy management, and limiting the reverse power flow (back into the grid). The results indicate that site controllers offer an efficient solution to manage the health of the connected assets and a scalable means to optimize the operations of a commercial customer with electrified transportation fleets.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2024

Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework

The secure integration and management of distributed energy resources (DER) and power aggregators in the electric grid requires secure communications and a physics-aware Command and Control (C2) strategy. A Blockchain (BC)-based overlay network was developed to provide a security layer for the existing power grid network that mitigates risks in current and legacy network and C2 protocols. By integrating a Model-Assisted Machine Learning (MAML) framework with a Secure Blockchain Overlay Network (SBON) a defense-in-depth strategy was achieved. In our approach, the MAML framework leveraged a smart contract framework to gather network data and learn the dynamics of DER to develop detection strategies for attacks targeting sensors and actuators used by DER. The MAML framework learned dynamical systems models for individual DERs to detect sensor attacks. For DER we utilized a Digital Twin (DT) to accelerate the learning process for a model resistant to stealthy attacks. The project created DT for PV inverters and BESS. The DTs were coupled with a model-assisted, data-driven learning of DER behavior. Specifically, we evaluated architectures for model-based learning with model-free fine-tuning. Additionally, differential privacy techniques were used to obfuscate data, while still allowing the computation of attack detection results based on obfuscated data. The SBON developed leverages a private permissioned blockchain network orchestrated with the Hyperledger Fabric framework. To connect the cyber world, which orchestrates the blockchain fabric, and the physical world where the power network resides, we developed a system implementation to enable the secure interaction of the physical world and the abstracted blockchain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Deep Reinforcement Learning for Autonomous Water Heater Control

Electric water heaters represent 14% of the electricity consumption in residential buildings. An average household in the United States (U.S.) spends about USD 400–600 (0.45 ¢/L–0.68 ¢/L) on water heating every year. In this context, water heaters are often considered as a valuable asset for Demand Response (DR) and building energy management system (BEMS) applications. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity cost of a water heater under a time-of-use (TOU) electricity pricing policy by only using standard DR commands. In this approach, a set of RL agents, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on an unseen pair of price and hot water usage profiles. The testing results showed that the RL agents can help save electricity cost in the range of 19% to 35% compared to the baseline operation without causing any discomfort to end users. Additionally, the RL agents outperformed rule-based and model predictive control (MPC)-based controllers and achieved comparable performance to optimization-based control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management using Smart Meters

This paper describes a systematic process of designing resilient electric distribution systems and microgrids using smart meters for surgical load management (SLM) as part of Advanced Metering Infrastructure (AMI). The work focuses on selection approach, integration, and interoperability aspects for AMI in microgrids. SLM is proposed as a granular control methodology for serving selective critical loads across different distribution feeders in the system during extreme events. The surgical load shedding as well as load pick-up provides a robust approach for maximizing critical load served in a resource-constrained electric distribution system or a microgrid. We present the case of a 20 MW islanded microgrid in Cordova, AK, USA, which is the demonstration site for field validation of resilience enhancement technologies for the DOE-funded Grid Modernization project RADIANCE. Cordova microgrid is an islanded distribution grid that provides an environment to prove the approach, and the techniques may also be applicable to other regional distribution systems.

microgrids↗
DOE OSTI2020

Optimal Energy Dispatch Controller for Fuel Cell-Integrated Multi-Zone Building

Stationary fuel cells provide potential opportunities for energy savings when integrated with buildings. Through smart dispatch of both electrical power and heat generated by the fuel cells and managing the building loads, the buildings can achieve more efficient operation. In this paper, we develop an optimal energy dispatch controller to operate a fuel cell-integrated building. The controller leverages the inherent thermal storage and the dispatchable fuel cell to reduce its operating cost and to allow the building to participate in grid services. The proposed controller is implemented on two types of commercial buildings, a large office building and a large hotel, and the effectiveness of the controller is demonstrated through simulations. The results also indicate that the potential saving varies significantly with different system parameters, including season, fuel prices, and equipment sizing, which provide helpful insights for building operators and other stake holders.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗
DOE OSTI2023

Clean Energy Microgrids: Considerations for State Energy Offices and Public Utility Commissions to Increase Resilience, Reduce Emissions, and Improve Affordability

In fall 2019, the National Association of Regulatory Utility Commissioners (NARUC) and the National Association of State Energy Officials (NASEO) initiated a joint Microgrids State Working Group (MSWG), funded by the U.S. Department of Energy (DOE) Office of Electricity (OE). The MSWG aims to bring together NARUC and NASEO members to explore the capabilities, costs, and benefits of microgrids; discuss barriers to microgrid development; and develop strategies to plan, finance, and deploy microgrids to improve resilience. This report, Clean Energy Microgrids: Considerations for State Energy Offices and Public Utility Commissions to Increase Resilience, Reduce Emissions, and Improve Affordability, focuses specifically on how clean energy microgrids can achieve both resilience and clean energy benefits. The paper provides an overview of the challenges faced by clean energy microgrids, outlines benefits that clean energy microgrids can provide, and details economic and cost considerations for the development of clean energy microgrid projects. Outlined in the paper are the necessary technological components of a clean energy microgrid, including generation, storage, energy efficiency measures, and smart controls. Current technologies are highlighted, along with potential configurations of clean technologies that are approaching cost competitiveness with commercially available options. The paper concludes with both policy and regulatory considerations for State Energy Offices and Public Utility Commissions to enhance the development and deployment of clean energy microgrids. Although it touches on the clean energy microgrids’ role in integrating distributed energy resources (DERs) into the larger grid, this is not the focus of this paper.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management Using Smart Meters: Preprint

This paper describes a systematic process of designing resilient electric distribution systems and microgrids using smart meters for surgical load management (SLM) as part of Advanced Metering Infrastructure (AMI). The work focuses on selection approach, integration, and interoperability aspects for AMI in microgrids. SLM is proposed as a granular control methodology for serving selective critical loads across different distribution feeders in the system during extreme events. The surgical load shedding as well as load pick-up provides a robust approach for maximizing critical load served in a resource-constrained electric distribution system or a microgrid. We present the case of a 20 MW islanded microgrid in Cordova, AK, USA, which is the demonstration site for field validation of resilience enhancement technologies for the DOE-funded Grid Modernization project RADIANCE. Cordova microgrid is an islanded distribution grid that provides an environment to prove the approach, and the techniques may also be applicable to other regional distribution systems.

microgrids↗