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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

DER as a service-ecoLong and VOLTTRON (Abstract)

The project goal is to commercialize the VOLTTRON-hosted “DER as a Service” (DaaS) application and make it an “out-of-the-box” solution for ecoLong to use as a secure residential energy management system that allows 1.) distributed energy resources (DERs) to participate in wholesale markets and provide services to the grid and 2.) intelligently control the energy in the residential buildings to the desired level while maintaining occupancy comfort. The product will be field deployed onto multiple Solar Liberty sites in New York state to demonstrate wide-scale participation of DERs in wholesale markets to provide services to the grid and validate the effectiveness of the solution. The integrated management of DERs and buildings increases the penetration of solar resources by managing its variability, providing grid services, and solving the evening ramping challenges. Ultimately, the DaaS platform will make buildings and DERs smarter by unlocking grid-interactive efficient buildings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Deep-Learning-Based Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment

Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.

building load forecasting↗
DOE OSTI2023

DER Digital Supply Chain Gap Analysis

Solar photovoltaic (PV) cybersecurity is a growing field of research. As deployments of solar PV have increased, cyber risk has also increased. Utility solar PV installations, however, are not required to comply with the North American Electric Reliability Corporation (NERC) Critical Infrastructure Protection (CIP) plan unless they meet a minimum generation threshold of 75 MW. Individual residential-scale solar PV deployments will not meet that generation threshold and are therefore excluded from the NERC CIP requirements. With most solar installations less than 75 MW, solar PV has been deployed with minimal oversight and highly variable cybersecurity maturity. The resources that comprise the digital supply chain can include software, code, data, and other digital components. But as clean energy technologies advance, cybersecurity threats and vulnerabilities continue to evolve and grow in sophistication. Supply chain cybersecurity represents a critical area for ensuring safe operations as the U.S. moves toward a clean energy future.

cybersecurity↗
DOE OSTI2026

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗
DOE OSTI2021

Clean Grid Vision: A U.S. Perspective - Chapter 2. Distribution Issues and Tools

The continued growth in distributed energy resources is fundamentally changing the way the distribution system is operated and planned. Additionally, an increasing number of grid issues are being regularly experienced by distribution engineers within an increasing number of utilities. Fortunately, these fundamental changes and increasingly regular issues are being addressed via continual improvements in existing distribution system modeling tools—for both tools used by industry and researchers—and via novel modeling methods, which are combining transmission and distribution system modeling to investigate new, often complex, system interactions at the transmission/distribution power system interface. As DERs continue to increase more and more utilities, regulators, and developers are finding usable solutions in the deployment of smart inverters with ever more capable functionalities. This increase in functionality is welcome but comes at the cost of more complex analysis when determining what specific settings should be used for an individual interconnection. With more time, experience, and likely the further development of advanced analysis tools, even higher levels of DER integration will result in a reliable, resilient, low-cost, and safely operating grid.

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DOE OSTI2021

Keystone Solar Future Project (KSFP)

The Keystone Solar Future Project (KSFP, also referred to as “Keystone Project” in the report) implements a cost-effective, secure, reliable, and safe technology platform that paves the way for future interconnected distributed energy resources (DER), creates a framework that enables high penetration of DER, and transforms the DER interconnection process. The project is important and necessary in a few aspects. First, the industry definition of Distributed Energy Resource Management System (DERMS) is not yet validated against field deployments and mostly implemented in small pilots relying on third party integration. Keystone project implements a direct plug and play communication to inverter based DER systems. Secondly, most interconnection application portal is not yet fully integrated with back-end system, thus lacks the capability to drive a complete and accurate modeling of DER assets into the planning and operational systems. Keystone project rolled out a fully integrated modeling process of DERs from interconnection to operational management. Lastly, customers were given an opportunity to learn about the advanced functions of the inverters and take full advantages of their benefits through participation in the pilot program. During the project, the technical effectiveness and economic feasibility of DER management were investigated and demonstrated in real life events and simulation studies. The project highlighted the importance of coordinated DER interconnection, installation and management with the rest of the distribution system.

14 SOLAR ENERGY↗
DOE OSTI2020

SunDial – An Integrated SHINES System to Enable High-penetration Feeder-level PV

The Project Team of Fraunhofer USA, National Grid, and IPKeys developed and conducted a pilot deployment of the SunDial system, a virtual power plant platform that enables high-penetrations of solar PV to be integrated into the distribution grid. The pilot was conducted over a 15-month period from August 2018 through October 2019 on a National Grid distribution feeder in Shirley, MA. A vendor-agnostic control platform (the “Global Scheduler”) optimally shaped the net load for a virtual portfolio of non-co-located DERs based on user-defined policy objectives. The goal of the SunDial project was to simplify and reduce the risk associated with the deployment of solar in high-penetration environments by: (1) Developing an open-source, vendor-agnostic dispatch platform that can be readily adapted to optimize control of DERs over a variety of use cases; (2) Developing auto-calibrating load and solar prediction methodologies that can be readily implemented and scaled to new deployments; (3) Developing a methodology to use demand-side management with traditional electrochemical energy storage to provide “load shaping” services in high solar penetration environments; (4) Using grid-scale storage to minimize short-term intermittency association with PV production; and (5) Deploying on the National Grid distribution system to gain experience on the potential for (and limits of) integrated storage with demand-side management.

14 SOLAR ENERGY↗
DOE OSTI2022

Controller Requirements for Managing Community Microgrids

Microgrid control systems are central to the functioning of a microgrid. They are responsible for managing distributed energy resources (DER) in both grid-connected and islanded modes of operation. Although microgrids are being developed and deployed by many utilities, several questions are being raised about the control system that manages them. This document provides the detailed list of requirements for a feeder-level microgrid controller to manage various islanded and grid-connected use cases. Functionally, the use cases include control scenarios that require the controller to maintain energy balance, prevent constraint violations, manage switching equipment, manage grid-forming (GFM) and grid-following (GFL) DER, manage critical/non-critical loads, and coordinate with peer systems to operate joined island areas. In addition to detailed requirements, the document includes interface and performance metrics for functional evaluation. These requirements can be applied to utility-managed microgrid controllers that exclusively manage utility-owned equipment; requirements also apply to third-party managed microgrid controllers that coordinate with the utility- and customer-owned equipment. The document can also be used by technology developers and project developers in industry to specify desired control strategies and performance characteristics for community microgrid controllers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Decentralised Reinforcement Learning for Dynamic Cyberattack Response in Microgrid Networks

Microgrids rely on communication networks for reliable operation, which makes them inherently vulnerable to cyberattacks. Such attacks can destabilise system dynamics and drive states away from their nominal operating trajectories. Although several physics-informed and machine learning-based strategies have been developed to counter these threats, the rapidly evolving cyber landscape enables adversaries to bypass static defences or rules-based mitigation approaches. This paper proposes a dynamic, online-trained and fully decentralised reinforcement learning (RL)-based cyberattack response framework to protect microgrids from evolving cyberattacks. The proposed framework deploys multiple deep Q-networks (DQNs), each associated with a distributed energy resource (DER), to enable localised and adaptive attack mitigation. In this framework, each DQN processes local voltage and frequency measurements—combined with intrusion detection system (IDS) alerts—as observations and rewards to guide decision-making. Extensive simulation studies demonstrate the robustness of the proposed framework under diverse attack scenarios and varying IDS-induced detection delays. Comparative analysis highlights its superiority over existing static or preexisting rules-based mitigation approaches. Finally, we present an analysis that shows the framework's scalability to real-life microgrids with more interacting agents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Cybersecurity Certification Standard for Distributed Energy Resources

Cybersecurity Certification Standard for Inverter Based Resources led by UL, and contributed to by NREL, is a certification standard for devices and their cyber security practices. The standard, which is being developed and led by UL, contains certification and testing processes for the devices to be certified before they are deployed in the field. The importance of the standard is to ensure that all DER devices have all the five pillars of cybersecurity, in which the baseline cybersecurity posture of the DER industry will be elevated.

certification standard↗
DOE OSTI2024

Federated Deep Reinforcement Learning for Decentralized VVO of BTM DERs

The future of grid control requires a hybrid approach combining centralized and decentralized methods to fully utilize the potential of smart edge devices with artificial intelligence (AI) capabilities. This paper aims to develop and evaluate a federated deep reinforcement learning (FDRL) framework for decentralized adaptive volt-var optimization (VVO) of behind-the-meter (BTM) distributed energy resources (DERs). First, this paper models a single deep reinforcement learning (DRL) agent using the Markov Decision Process (MDP) framework for decentralized adaptive VVO of BTM DERs. Two DRL algorithms, soft actor-critic (SAC) and twin-delayed deep deterministic policy gradient (TD3), are compared for their effectiveness in optimizing VVO. Results show that TD3 outperforms SAC, achieving a 71.3% improvement in mean reward. Finally, the DRL agent is deployed within the FDRL framework, using the Flower platform, to enhance learning, provide adaptive control, and ensure data privacy for BTM DERs.

Ravi, Abhijith↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

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DOE OSTI2020

Assessing DER Network Cybersecurity Defences in a Power-Communication Co-Simulation Environment

Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface. Maloperation or malicious control of DER equipment can now cause substantial disturbances to grid operations. Fortunately, many options exist to defend and limit adversary impact on these newly-created DER communication networks, which typically traverse the public internet. However, implementing these security features will increase communication latency, thereby adversely impacting real-time DER grid support service effectiveness. In this work, a collection of software tools called SCEPTRE were used to create a co-simulation environment where SunSpec-compliant PV inverters were deployed as virtual machines and interconnected to simulated communication network equipment. Network segmentation, encryption, and moving target defence security features were deployed on the control network to evaluate their influence on cybersecurity metrics and power system performance. The results indicated that adding these security features did not impact DER-based grid control systems but improved the cybersecurity posture of the network when implemented appropriately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks

Rapid and accurate detection and localization of electronic disturbances simultaneously are important for preventing its potential damages and determining potential remedies. Existing anomaly detection methods are severely limited by the low accuracy, the expensive computational cost and the need for highly trained personnel. There is an urgent need for a scalable online algorithm for in-field analysis of large-scale power electronics networks. Here in this paper, we propose a fast and accurate algorithm for anomaly detection and localization of power electronics networks: stratified colored-node graph (CONGO2). This algorithm hierarchically models the change of correlated waveforms and then correlated sensors using the colored-node graph. By aggregating the change of each sensor with its neighbors’ inputs, we can spontaneously identify and localize the anomaly that cannot be detected by data collected from a single sensor. As our proposed method only focuses on the changes within a short time frame, it is highly computational efficient and only needs small data storage. Thus, our method is ideal for online and reliable anomaly detection and localization of large-scale power electronic networks. Compared to existing anomaly detection methods, our method is entirely data-driven without training data, highly accurate and reliable for wide-spectrum anomalies detection, and more importantly, capable of both detection and localization. Thus, it is ideal for infield deployment for large-scale power electronic networks. As illustrated by a distributed energy resources (DERs) power grid with 37-node, our method can effectively detect and localize various cyber and physical attacks.

42 ENGINEERING↗
DOE OSTI2020

Cyber-physical Resilient Interoperable Microgrid Networks

The paper presents the results of an industry-academic collaboration between ABB, Duke Energy and the University of Illinois at Urbana-Champaign (UIUC) that has developed and demonstrated a cyberphysical resilient control and communication architecture for deployment of multiple microgrid networks, as well as retrofitting the existing distribution grids by increasing DER penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Energy Resilient Recovery in Puerto Rico: Hurricane Maria Recovery Support

This report covers microgrids as a special application of distributed energy resources (DERs) in Puerto Rico. This is one of a series of reports describing the U.S. Department of Energy (DOE) multi-laboratory efforts undertaken. To ensure the sustainable, long-term recovery of Puerto Rico's electric power grid from hurricanes Maria and Irma and to build capacity to manage future potential natural disasters in the most secure and resilient way, DOE convened experts from multiple national laboratories to develop a comprehensive set of data, models, analytic tools, and studies, considering inputs from a wide variety of stakeholder groups, to support technically sound recommendations for Puerto Rico's energy investment decisions. In Phase 1 of the multi-laboratory effort to support Puerto Rico's recovery, the National Renewable Energy Laboratory (NREL) provided the utility company Puerto Rico Electric Power Authority (PREPA) recommendations for a new framework of interconnection standards to accelerate the integration of utility-scale, transmission-connected, renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliability, safety, or security (https://www.nrel.gov/docs/fy19osti/73848.pdf). In Phase 2, NREL published a report focused on the interconnection of distributed energy resources (DERs) to the electric distribution system in Puerto Rico (https://www.nrel.gov/docs/fy21osti/77127.pdf). This report familiarized the reader with Puerto Rico's distribution infrastructure and operational practices and procedures that are relevant to DER interconnection. The report also provided considerations for streamlining the interconnection process given the expected increase in deployments resulting from Puerto Rico's renewable portfolio standard goal of 100% renewables by 2050. Accordingly, the report identifies considerations and concerns associated with the increase in intermittent generation, strategies for DER interconnection best practices, and the potential use of the latest technological solutions identified in the latest revision of the Institute of Electrical and Electronics Engineers 1547-2018 interconnection standard. Additionally, the report identified ways to improve the physical resiliency of installed DERs. This task describes how distributed energy systems may participate in and contribute to improving the resiliency of Puerto Rico's energy infrastructure in the future. This report presents an analysis of the Puerto Rico grid to illustrate the possible different microgrid and minigrid scenarios. The capability to form sustained microgrids and minigrids has the potential to provide a high level of resiliency during disturbances on the grid. DERs, on the other hand, have the capability to aid in the microgrid operation by providing grid support as well as grid-forming functionality. Other tasks in Phase 3 include voltage regulation in distribution networks using DERs and transmission-and-distribution co-simulation.

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