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Product Abstract

Distributed Energy Resources and Management of Future Distribution

Product ID:1020832
Date Published:25-Mar-2010
Sector Name:Power Delivery & Utilization - Distribution & Utilization
Document Type:Technical Results
Price:No Charge

This Product is publicly available

   1.08 MB - Adobe PDF (.pdf)

The Electric Power Research Institute's (EPRI's) Smart Grid demonstration initiative is a collaborative research effort focused on the design, implementation, and assessment of field demonstrations to address challenges with integrated distributed resources in grid and market operations as well as system planning.

The main objective of this study is to identify approaches to interoperability and integration that can be used on a systemwide scale to help standardize the use of distributed energy resources (DER) as part of overall system operations and control.


The objectives of this study are as follows:

  • Develop an end-to-end model depicting the data and information exchange required to manage the large-scale deployment of DER between systems involved in regional system operations, transmission, distribution, and customer service down to end-use energy systems and on-site resources.

  • Characterize the current baseline state of typical existing “legacy” systems for managing DER equipment.

  • Define the future state of these systems, including the functions and requirements necessary to scale up and manage widely deployed DER.

  • Identify the gaps between the current and future states.

  • Identify the benefits associated with the future state, including the benefits of a mature management infrastructure that covers interoperability and security.

  • Define a strategy for migrating from a legacy system to the future state and associated architecture considerations.

The challenges of the study lie in the transition state of Smart Grid and its components. Among these challenges are DER and the renewable energy-based components.


The study is based on the conceptual design of major advanced DA applications introduced in the IntelliGrid project and related studies and updated in accordance with the most recent development in the Smart Grid area, including the National Institute of Standards and Technology (NIST) Interoperability Roadmap. The study addresses the information support and controlling capabilities of DA applications available under the current conditions and the possible development of information support and controls by integrating DER as information sources and as controllable variables in the DA applications. Prior work performed by Utility Consultants International was used in the development of this report.


The study includes discussions on advanced distribution automation applications in the Smart Grid environment with integration of DER as active participants of power system operations. In addition, the potential benefits of integrating DER into dynamic optimization are analyzed and existing and future requirements for information exchange with DER are addressed. Views on the actors, logical interfaces, and object models involved in this information exchange are also presented. The gaps between the current and future states of the information exchange with DER are described, and the migration strategy to overcome the gaps is outlined. The report concludes with recommendations for future work.

Application, Value and Use

This study can serve as a reference for feasibility studies in Smart Grid operations and for the development of a Smart Grid data management system, object model, and information exchange designs. The material presented in this report should be used for the selection, expansion, integration, and harmonization of interoperability standards.

EPRI Perspective

This project takes a future view of a few advanced distribution automation (DA) functions and uses these to further the development of the open standards necessary to enable these forward-looking applications. This study addresses the use of multiple distributed energy resources as dependent, as well as independent, variables in the dynamic optimization of power system operations. Because there are no precedents of such optimization in real utilities, this study represents a new step into future grid operations.
2010 Program 161   Information and Communication Technology
  • Distribution Automation
  • Distributed Energy Resources
  • Smart grid
  • Microgrids
  • Operation models
  • Electric storage

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