Energy Grid Ontology for Digital Twins is Now Available

Published May 06 2021 08:00 AM 11.6K Views

Last year, we announced the general availability of the Azure Digital Twins platform. The associated open modeling language, Digital Twins Definition Language (DTDL), is a blank canvas which can model any entity. It is therefore important to provide common domain-specific ontologies to bootstrap solution development and enable developers to quickly model and create sophisticated digital representations of connected environments like buildings, factories, farms, energy networks, railways, stadiums, and cities, then bring these entities to life within a live execution environment that integrates IoT and other data sources.

Earlier this year, we published the open-source Smart Buildings and Smart Cities ontologies for digital twins. Today we published the open-source Energy Grid Ontology for digital twins, an open-source GitHub repository. This will help solution providers accelerate development of digital twin solutions for energy use cases (monitoring grid assets, outage and impact analysis, simulation, and predictive maintenance) and facilitate digital transformation and modernization of the energy grid.


Domain ontologies founded upon industry standards are a foundational catalyst to developing global-scale, interconnected solutions. Microsoft collaborates with customers, domain experts, and industry standards organizations to adapt existing industry data models and best practices to DTDL. The smart buildings ontology is based on RealEstateCore, and the smart cities ontology is based on ETSI CIM NGSI-LD data models defined under the Smart Data Models initiative. Today, we are releasing the energy grid ontology adapted from the Common Information Model (CIM)[1], a global standard for energy grid assets management, power system operations modeling and physical energy commodity market. The CIM-based DTDL ontology provides a contextual understanding of data by identifying the properties, capabilities, and telemetry of various grid entities as well as the relationships between them. Power & Utilities customers and partners can leverage as well as extend this open-source repository for their solutions and contribute their learnings to the repository for others to benefit.


CIM organizes grid assets and entities into distinct packages. In this first iteration, we have included core, wire, and generation packages, and prosumer-related entities from metering, customer, and Distributed Energy Resource (DER) packages. We have been working together with an extended team, including Agder EnergiStatnettSirus, and FIWARE Foundation (founder of the Smart Data Models initiative). We started with the below packages based on current and upcoming solutions that utilize these models:   

  • Core Package contains PowerSystemResource, ConductingEquipment, and common collections of those entities shared by all applications. Most of the other packages have associations with and generalizations that depend on the core package.
  • Wire Package is an extension to the Core that provides model information detailing the electrical characteristics of transmission and distribution networks. This package is used by network applications, such as state estimation, load flow, and optimal power flow. 
  • Generation Package has information for unit commitment and economic dispatch of hydro and thermal generating units, load forecasting, automatic generation control, and unit modeling for training simulation.
  • Prosumer Package included a compilation of various entities related to consumer and DER from the current CIM packages. For example, EquivalentLoad, UsagePoint, and MeterReading.

With this release of the Energy Grid Ontology for digital twins, we've focused on an initial set of models, and we welcome you to contribute to extend the initial set of use cases, as well as improve the existing models.


Energy grid DTDL model adapted from CIMEnergy grid DTDL model adapted from CIM 


Partner adoption

DTDL is an open modeling language based on JSON-LD and RDF, with which developers can define the schema of the entities they expect to use in their graphs or topologies. Many partners and customers have already been leveraging this CIM-based DTDL grid ontology in developing their Azure Digital Twins solutions.


For example, Agder Energi implemented DTDL models of various DERs and their distribution network entities, such as substations, feeders and pole transformers, in the smart grid project. These additional CIM models will enable Agder Energi to develop new capabilities, such as power flow analysis and real-time grid operations.


XMPRO has been piloting multiple energy monitoring and controlling scenarios. Their Data Stream Designer allows users to contextualize streaming data using digital twin models that enhance visualization and recommendations in the App Designer dashboards.


Siemens MindSphere City Graph, a multi-award-winning digital twin solution, offers innovative ways to optimize city operations. Through  creating and modeling of urban space digital twins, cities are able to monitor, control and manage their physical infrastructure. MindSphere City Graph is powered by Azure Digital Twins. It leverages NGSI-LD based DTDL ontology for city entities and CIM-based DTDL grid ontology for power & utilities use cases, such as with Aspern Smart City Research.


As part of our commitment to openness and interoperability, we also continue to promote best practices and shared digital twin models for customer scenarios through the Digital Twin Consortium open-source collaboration initiative and continuing our collaboration with the FIWARE Foundation in connection with the Smart Data Models initiative.  


Call to action

We invite you to leverage the energy grid ontology GitHub repository with your energy Digital Twins solutions and to contribute to it by filing issues and sending pull requests.


By providing common domain ontologies our goal is to bootstrap solution development and enable developers to quickly model and create sophisticated digital experience of connected environments like buildings, factories, farms, energy networks, railways, stadiums, and cities, then bring these entities to life within a live execution environment that integrates IoT and other data sources.


Explore, leverage, and contribute to buildings, cities, and grid ontologies and develop integrated solutions across these domains.


Learn more about ontology and model concepts.



[1] This is an IEC TC57 Standard and is promoted by the UCAIug CIM User Group.  The UCAIug is a membership-based user group for the IEC TC57 standards as well as the OpenFMB standards.  Many documents, models, and other artifacts surrounding the CIM can be found at

Version history
Last update:
‎Sep 14 2021 09:02 AM