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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microgrid Energy Management System Integration with Advanced Distribution Management System

The Integrated Distribution Management System (IDMS) project was initiated to demonstrate the interactive operation of microgrid systems and the distribution systems with which they interconnect. The key technologies for this are the microgrid management system and the utility distribution management system. The IDMS project successfully demonstrated that a utility’s advanced distribution management system/distributed energy resources management system (ADMS/DERMS) could effectively manage microgrids to provide visibility and control functionalities as well as use the microgrid as a dispatchable resource to support the utility grid. The DERMS accomplishes this by determining active and reactive power needs at the point of common coupling (PCC) using advanced applications like volt/VAR watt optimization (VVWO) and load relief (LR) with the underlying core applications state estimation (SE) and load flow (LF). The ADMS/DERMS can use the microgrid as a resource to resolve and prevent violations in the grid and to optimize the operational working state of the grid. The IDMS project demonstrated that a utility-operated ADMS with embedded DERMS functionality can flexibly manage a variety of microgrids and other aggregated distributed energy resources (DER) in concert with the wider distribution grid. Microgrids can provide grid services in any number of different ways to meet the operational needs of the distribution utility. The manner of aggregation — microgrid or virtual power plant — is not necessarily relevant to the utility as long as the grid services from the aggregated DER are available and can be managed by its ADMS/DERMS for the stability and reliability of the grid. The IDMS project demonstrated this integrated ADMS concept by combining hardware/software-in-the-loop testing with commercial products from different vendors and a utility’s network model. The project integrated the Schneider Electric EcoStruxure™ ADMS with DERMS with the Schweitzer Engineering Laboratories (SEL) POWERMAX ® Microgrid Control System, and the simulated resources with energy company PECO’s model of a utility-owned microgrid, establishing an operational relationship in which the utility manages the operational functionality of a microgrid at the PCC and that provides the utility with the capability to control the comprehensive power system, inclusive of the macrogrid and microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Optimal Energy Dispatch of Distributed PVs for the Next Generation of Distribution Management Systems

Advanced Distribution Management Systems (ADMS) are being widely adopted by electric utilities for managing and optimizing the operations of their distribution systems. Distributed photovoltaic (DPV) systems with smart inverters can be controlled to adjust active power and reactive power outputs, and they are envisioned to become a part of (centrally or distributed) controllable assets managed by the ADMS for optimizing grid operations. This paper proposes an optimal energy dispatch strategy controlling DPV systems for regulating distribution voltages and achieving conservation voltage reduction. A convex optimization model is proposed with the use of linearized power flow, and the gradient projection algorithm is used to solve the optimal active power and reactive power outputs of smart inverters. The proposed optimal energy dispatch is implemented using an open-source ADMS platform, and simulation results have demonstrated the effectiveness of the proposed approach on improving distribution grid operations.

42 ENGINEERING↗
DOE OSTI2016

Price Based Local Power Distribution Management System (Local Power Distribution Manager) v1.0

A trans-active energy micro-grid controller is implemented in the VOLTTRON distributed control platform. The system uses the price of electricity as the mechanism for conducting transactions that are used to manage energy use and to balance supply and demand. In order to allow testing and analysis of the control system, the implementation is designed to run completely as a software simulation, while allowing the inclusion of selected hardware that physically manages power. Equipment to be integrated with the micro-grid controller must have an IP (Internet Protocol)-based network connection and a software "driver" must exist to translate data communications between the device and the controller.

BROWN, RICHARDE.↗
DOE OSTI2017

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, Implementation Strategy for a Distribution Management System

Electric distribution utilities encounter many challenges to successful deployment of Distribution Management Systems (DMSs). The key challenges are documented in this report, along with suggestions for overcoming them. This report offers a recommended list of activities for implementing a DMS. It takes a strategic approach to implementing DMS from a project management perspective. The project management strategy covers DMS planning, procurement, design, building, testing, Installation, commissioning, and system integration issues and solutions. It identifies the risks that are associated with implementation and suggests strategies for utilities to use to mitigate them or avoid them altogether. Attention is given to common barriers to successful DMS implementation. This report begins with an overview of the implementation strategy for a DMS and proceeds to put forward a basic approach for procuring hardware and software for a DMS; designing the interfaces with external corporate computing systems such as EMS, GIS, OMS, and AMI; and implementing a complete solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Test Bed to Evaluate Advanced Distribution Management Systems for Modern Power Systems

This paper presents a test bed that utilities, vendors, and researchers can use to evaluate the performance of existing and emerging advanced distribution management systems (ADMS) or specific applications of such systems. The test bed provides a realistic laboratory test setting, including detailed modeling of the power system, controller and/or power hardware, and industry-standard communication protocols. The test bed can further represent the current state of a specific utility's distribution system or the anticipated state with increased penetrations of distributed energy resources, such as rooftop photovoltaic systems, residential battery energy storage systems, electric vehicles, and loads with smart controls. The paper describes the design and implementation of the test bed. We present two use cases of the test bed and preliminary results for these two use cases. We also discuss upcoming and potential future use cases. Results from test bed experiments are intended to accelerate industry deployment of ADMS technologies and advance development of ADMS capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Test Bed to Evaluate Advanced Distribution Management Systems for Modern Power Systems: Preprint

This paper presents a test bed that utilities, vendors, and researchers can use to evaluate the performance of existing and emerging advanced distribution management systems (ADMS) or specific applications of such systems. The test bed provides a realistic laboratory test setting, including detailed modeling of the power system, controller and/or power hardware, and industry-standard communication protocols. The test bed can further represent the current state of a specific utility's distribution system or the anticipated state with increased penetrations of distributed energy resources, such as rooftop photovoltaic systems, residential battery energy storage systems, electric vehicles, and loads with smart controls. The paper describes the design and implementation of the test bed. We present two use cases of the test bed and preliminary results for these two use cases. We also discuss upcoming and potential future use cases. Results from test bed experiments can be used to accelerate industry deployment of ADMS technologies and advance development of ADMS capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advance Distribution Management System (ADMS)

This presentation explores the transition from traditional distribution management systems to Advanced Distribution Management Systems (ADMS) as a foundation for smart grid development. It highlights the key benefits of ADMS, including enhanced reliability, improved operational efficiency, and increased situational awareness. The presentation also addresses common implementation challenges such as system integration, data management, and organizational readiness. It concludes with a forward-looking perspective on the evolving role of ADMS and essential takeaways for utilities and stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Digital twin advanced distribution management systems (ADMS) and methods

Advanced Distribution Management Systems not generally optimize over the entire feeder because there are few high-fidelity distribution circuit models and real-time distribution-connected sensors are rare. The limited observability at the distribution level makes it difficult to globally optimize distribution operations and issue control setpoints to power systems equipment or Distributed Energy Resources (DER) to perform grid-support services. For example, setpoints can be issued to DER based on results from an optimization module that incorporates a static or time-series feeder simulation. Feeder simulation initial conditions are populated with photovoltaic (PV) and load forecasts, state estimation results, and/or digital twin measurements or state output. The real-time (RT) digital twin runs a model of the feeder to generate state estimation pseudo-measurements since there are limited live feeder measurements.

Johnson, Jay Tillay↗
DOE OSTI2022

NREL's Advanced Distribution Management System (ADMS) Test Bed

Transform utility electric distribution management systems to enable the integration and management of all assets and functions across the utility enterprise regardless of vendor or technology. Four program areas: Platform: Develop an open-source platform; evaluate advanced applications. Test bed: Build a vendor-neutral test bed to evaluate existing and future advanced distribution management system (ADMS) functionalities in a realistic setting. Applications: Develop an initial suite of ADMS applications. Advanced control: Develop new integrated optimization and control solutions.

ADMS test bed↗
DOE OSTI2020

NREL's Advanced Distribution Management System (ADMS) Test Bed

NREL's advanced distribution management system (ADMS) test bed is a vendor-neutral resource for evaluating existing and future ADMS functionalities in a realistic laboratory setting. The test bed uses Opal-RT's ePHASORsim and eMEGAsim products interfaced with an OpenDSS power system simulation through the HELICS cosimulation platform developed by multiple DOE laboratories; and with power and controller hardware. NREL will present an overview of the test bed and the technologies included within it, and also some examples of how the test bed has been used to address industry challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

NREL's Advanced Distribution Management System (ADMS) Test Bed

NREL's advanced distribution management system (ADMS) research helps utilities meet customer expectations of reliability, power quality, renewable energy use, data security, and resilience to natural disasters and other threats.

Advanced Research on Integrated Energy Systems↗
DOE OSTI2015

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization

This report describes the application functions for distribution management systems (DMS). The application functions are those surveyed by the IEEE Power and Energy Society’s Task Force on Distribution Management Systems. The description of each DMS application includes functional requirements and the key features and characteristics in current and future deployments, as well as a summary of the major benefits provided by each function to stakeholders — from customers to shareholders. Due consideration is paid to the fact that the realizable benefits of each function may differ by type of utility, whether investor-owned, cooperative, or municipal. This report is sufficient to define the functional requirements of each application for system procurement (request-for-proposal [RFP]) purposes and for developing preliminary high-level use cases for those functions. However, it should not be considered a design document that will enable a vendor or software developer to design and build actual DMS applications.

Wang, Jianhui↗
DOE OSTI2017

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, Business Case Calculations for DMS

Distribution Management System (DMS) applications require a substantial commitment of technical and financial resources. In order to proceed beyond limited-scale demonstration projects, utilities must have a clear understanding of the business case for committing these resources that recognizes the total cost of ownership. Many of the benefits provided by investments in DMSs do not translate easily into monetary terms, making cost-benefit calculations difficult. For example, Fault Location Isolation and Service Restoration (FLISR) can significantly reduce customer outage duration and improve reliability. However, there is no well-established and universally-accepted procedure for converting these benefits into monetary terms that can be compared directly to investment costs. This report presents a methodology to analyze the benefits and costs of DMS applications as fundamental to the business case.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, DMS Integration of Distributed Energy Resources and Microgrids

Deregulation of the electric utility industry, environmental concerns associated with traditional fossil fuel-based power plants, volatility of electric energy costs, Federal and State regulatory support of “green” energy, and rapid technological developments all support the growth of Distributed Energy Resources (DERs) in electric utility systems and ensure an important role for DERs in the smart grid and other aspects of modern utilities. DERs include distributed generation (DG) systems, such as renewables; controllable loads (also known as demand response); and energy storage systems. This report describes the role of aggregators of DERs in providing optimal services to distribution networks, through DER monitoring and control systems—collectively referred to as a Distributed Energy Resource Management System (DERMS)—and microgrids in various configurations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)

Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.

Blonsky, Michael↗