Microgrid Digital Twins and IoT

Microgrid Digital Twins and IoT

In CROM, this research and innovation area comprises the following frameworks:

MG DT and IoT RoadMap

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Following Industry 4.0, the forth-industrial revolution, and with the recent advances in information and communication technologies, digital twinning concept is attracting the attention of both academia and industry across sectors. According to Industry 4.0, the next-generation systems are the outcome of the evolution and convergence of new technologies such as onboard computation, advanced controllers, big data analytics, machine learning, and IoT. Adopting digital twinning concept, the real-time data streams from physical assets can be continuously gathered, processed, and analyzed along with the high-fidelity models to establish a digital mirror of complex physical systems and provide a great insight into their current and future operating status that can be used for real-time supervisory and control.

Digital twins (DTs) are defined as digital representations of potential or actual physical systems (assets) that are connected to the real counterpart via reliable communication links to establish bi-directional data exchange to present a dynamic, precise, and up-to-date model of the physical system (asset). Although the birthplace of twinning is in aerospace and aviation industries, DT rapidly found its applications in manufacturing, healthcare system for elderly healthcare services and remote surgery, urbanization and smart cities, petrochemical, automotive, and power systems.

Digital Twin for Power Systems

The need for DT in MGs arose due to the growing complexity of systems and equipment, which require close inspection and timely maintenance. Specially, those assets, which are not easily accessible, require real-time remote monitoring and predictive maintenance. The increasing penetration of RESs into the MGs and the emergence of prosumers are also demanding accurate dynamic forecasting techniques as well as automatic learning of behavioral patterns of prosumers. Finally, the growing dependency of other critical infrastructures such as healthcare, transportation, telecommunication, water systems, etc. on electric systems demands a highly reliable supply of energy with the minimum service interruption and downtime. 

MGDT will support the accurate prediction of RESs power supply and prosumers’ behavior taking advantage of well-structured historical and real-time data and high-fidelity models. Benefitting from the enhanced situational awareness and predictive maintenance provided by MGDTs, the MGs’ resilience can be noticeably improved and the system/asset lifetime can be broadly extended. Accordingly, MGDTs will reduce the cost, optimize the performance of the underlying physical systems, and enhance the sustainability of the next-generation MGs.


At present, new market, regulatory structures and new energy services in the smart grid seems to be the response to profound changes in the way that energy should be generated, stored, distributed, managed and finally consumed. What makes the global challenge particularly severe is the essential role that energy is playing as a whole. In fact, ecological and sustainability awareness, comfortā€oriented consumers’ behavior, etc., are the factors which are becoming more and more complex to address especially when there is a massive input of smart devices combined with multiple operating systems taking into account interoperability and compatibility issues.

On the other hand, the world is changing rapidly thanks to the technology revolution having an enormous impact on our daily lives at work and at home. In fact, in conjunction with the Fourth Industrial Revolution (Industry 4.0), Internet of Things (IoT) paradigm seems to increase the visibility of energy consumption by providing intelligent and automated systems to improve comfort and energy efficiency through comprehensive solutions for connectivity, manageability, and security in the future smart grids.If there is an adaptation on the behavior of the prosumer devices based on the information that they receive such as electricity price, then energy consuming/producing devices will not be black boxes but can be adapted accordingly instead.

IoT- Enabled Home Energy Systems


NEW IOT Core components and adapters

The VICINITY Cloud enables IoT infrastructure operators and Service providers to configure a virtual neighbourhood of connected devices and value-added services including the setup of sharing access rules between them through the user-friendly interface of VICINITY Neighbourhood Manager. Configuration of the virtual neighbourhood and sharing access rules are used by VICINITY Communication Server to setup communication channels between each VICINITY Node to control exchange of user data. IoT infrastructure operators and Service providers can search for devices and services in virtual neighbourhood based on semantic description of device properties, actions, events and service products & required inputs stored in semantic repository. Moreover, IoT operators, System integrators and Services providers can register the VICINITY Nodes (registration of the application API) to communication in peer-to-peer. The selected VICINITY Neighbourhood Manager functionalities are available through VICINITY Neighbourhood Manager API as well. The API can be used by any value-added services to improve the user experience for its end-users.

A VICINITY Node is the set of software components which maintains the user data exchange between peers in the VICINITY P2P network based on configuration of the virtual neighbourhood and sharing rules received from VICINITY Communication Server. For that purpose, VICINITY Node consists of the following 3 main components:

  • VICINITY Gateway API and Communication Node;
  • VICINITY Agent;
  • VICINITY Adapter.

The VICINITY Adapter, which is a component provided by IoT infrastructure owner or respective system integrator, aims to simplify the adoption of IoT infrastructure in as simple way as possible. There are various adapters are developed, for instance, FIWARE-NGSIv2 adapter to offer access to a countless number of off-the-shelf IoT infrastructures based on this well-known framework, IoTivity framework adapter, Gorenje smart appliance adapters, IKEA light bulb adapter, and so on. The LabVIEW adapter is developed by AAU for AAU Energy Value Added Services.

IoT core components and adapters

Cross Domain Pilot Sites

The VICINITY platform is demonstrated on many different real-case scenarios, addressing cross-domain applications (Smart energy, Smart building, Healthcare and Mobility domains), showing the applicability of the proposed solution in different IoT ecosystems and revealing the value-added services that are achieved.

In particular, the four domains are being directly affected by the ongoing new market design in energy sector, new models introduction through digitalization in health and building domains and related customers’ requirements driven changes in transport domain.

The IoT Microgrid Living Laboratory - IoT-MGLab

The IoT-MGLab is a living demonstration laboratory that aims to implement and demonstrate cost-effective and comfort-aware energy solutions for future smart homes and buildings. This facilitiy enables an internet of things (IoT)-based infrastructure for a data intensive system and its interaction with end-users.
The laboratory also serves as a demonstrator to show the viability of low voltage DC and AC systems for future households which will enhance the energy efficiency, flexibility and reliability following Danish smart grid strategy.

CROM IoT Core Areas and Facilities

*CLICK ON THE IMAGE FOR A 360°LAB TOUR IoT Microgrid Laboratory



Collaborative Partners and Sponsors



Selected Publications