Smart Energy Systems Laboratory

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“Smart Grid Laboratories Inventory 2018” report by Joint Research Centre, European Commission


  We are proud to announce that the Smart Energy Systems
  Laboratory at the department   is included in “Smart Grid
  Laboratories Inventory   2018” report   by  Joint Research
  Centre, European Commission. The survey covers 89
  labs worldwide from which 69 are located in Europe and        20 outside. Our  laboratory is the only research facility            listed for Denmark.


Across the world, intelligent energy systems (coupling major energy sectors like electricity, thermal and transportation) are considered as a key solution to promote clean energy, improve efficiency and costs. Intelligence across systems is a strict requirement to transform the system planning and energy strategies for environmental friendly and sustainable future. However, there are only few smart energy installations or real-time systems that allow to experience the challenges and develop the required standards for the business. In order to realize the energy balance and economic benefits in a system with high penetration of renewables, increasing demand, flexible loads, increased transmission capacity, international trading and new actors, a close synergy between energy vectors is foreseeable. The main aspects of such intelligent energy systems are the ICT infrastructure, energy networks and systems itself. The research and development activities in this area need to account for actual control and communication layers upon a realistic model of the energy networks and systems, which requires scientific expertise as well as highly specialized hardware and software.

The Smart Energy Systems Laboratory is a multidisciplinary cyber-physical system that captures all domains, layers and zones from the Smart Grid Architecture Model (SGAM) in a Real-Time Hardware-In-the-Loop framework. It enables the Model Based Design approach for intelligent energy systems analytics and functionalities.

Smart Energy Systems Laboratory



Component Layer

Opal-RT based Real Time Digital Simulator for large power grids and other energy networks. The discrete simulator can host models for detailed power electronic converters as well as large power grids both EMT (up to 2000 electrical nodes) and RMS (up to 5000 three-phase buses) including detailed or aggregated generation and consumption units. A four quadrant grid simulator is coupling the Real-Time Digital Simulator with physical components e.g. PV panel emulator and Li-Ion battery connected through a dual DC port inverter to grid, flexible three-phase loads for emulation of household consumption and a large renewable based dispersed generator. Development and testing of advanced grid monitoring solutions is available using dedicated industrial solutions.

Information and Communication Layers

Dedicated hardware and software is used to emulate networks (xDSL, RF, GPRS, 3G, LTE, etc.) including stochastic modelling of data traffic and trace based data traffic generation. Data collection mechanisms for Advanced Metering Infrastructure, RTUs and other types of measurement sources are virtually emulated or implemented using off-the-shelf solutions (EFACEC data concentrator). Every device in the setup is synchronized with NTP to a dedicated GPS synchronized device, achieving time synch in the order of few milliseconds. Furthermore, the setup supports delay emulation between SGAM layers, depending on application. This allows the use of existing protocols such as TCP/UDP, OpenADR, DLMS and IEC standards (such as IEC60870-104, IEC 61850 MMS/Goose/SV), to be exposed to controlled network delays, as well as providing an environment where one can experiment with the effects/impact of cyber security threats in smart grid applications.

Function Layer

Various aggregator and supervisory controls e.g. hybrid power plant control, microgrid control, economic dispatch and unit commitment, energy management, Run-Time Distribution Grid State Estimation,  etc. are implemented and distributed among various host platforms according to desired applications. Bachmann’s PLCs, Raspberry PI or PCs running Real Time Desktop are connected to Component Layer using the laboratory LAN (ICT Layer).

Business Layer

Functionalities at market and enterprise level such as database for historical profiles, energy market participation, generation and load forecast, asset management (e.g. outage diagnosis, loss estimation, etc. are also implemented and distributed among various real-time computing platforms. GIS mapping based visualization similar to real operational centers is collecting and presenting data from downstream layers.

Smart Energy Systems Laboratory

Special equipment and tools

  • Four quadrant 50 kVA grid simulator (voltage asymmetries and flickers, harmonics and interharmonics up to 3 kHz, etc.)
  • Four quadrant emulator for dispersed generation (±20 kW/±10 kVAR). This component comprises of a grid converter and a DC supply/sink controlled by a dSpace system. It offers high flexibility in developing and testing control algorithms for grid side converter, possibility to implement various renewable sources e.g. wind generator, solar PV and different energy storage technologies including the energy management. The system is remotely controlled by upper hierarchical levels.
  • PV Panel and Battery. A 6 kWh Li-ion battery and a 3 kW PV-panel emulator are connected to the grid using a commercial 4 kW grid-connected solar inverter. The PV-panel emulator is capable of emulating various types of PV arrays in various operating conditions, such as variable solar irradiance and different grades of shading. The PVES system offers various options for energy management, such as charging the battery from either grid or PV-panel emulator, keeping the battery state of charge in a certain range and limiting the power consumed from the battery or grid in certain limits.
  • Flexible AC loads. Three programmable AC loads (2.8 kW) are emulating the usual household consumption. Pre-defined profiles based on real measurements or probabilistic models can be used. Another single phase 4.5 kW unit is also available for emulating special loads e.g. heat-pumps, electric boilers, etc.
  • Dual CPU PC for high computational tasks
  • Extensive collection of real-time models:
    • Generic IEEE 12-bus including large frequency excursions and swing modes.
    • Hybrid/wind power plants layouts based on commissioned systems.
    • Several medium and low voltage distribution grids based on Danish use cases.
    • Toolbox for generating statistical load profiles for households
    • Toolbox for renewable generation and energy storage systems with various model granularities

Features & services

  • Running Real-Time HIL applications
    • Asset Management e.g. outage detection, loss calculation, state-estimation, etc.
    • Demand Response in distribution grids
    • Coordinated control of Renewable Generation Plants in distribution grids
    • Provision of ancillary services from hybrid/wind power plants
    • Power and energy management in off-grid systems
  • Developing, testing and validate hierarchical control, energy management and dispatch solutions for hybrid renewable plants and smart grid applications considering the ICT impact at Technology Readiness Level 6
  • Compliance testing of power converter based devices including control strategies using Power HIL approach
  • Assessing impact of high renewable penetration scenarios in distribution grids including ICT aspects
  • Assessing impact of cyber security threats in smart grid applications.

Sponsors and collaborators

Safety information

Special safety measures are applied to the Lithium-Ion battery system i.e. special fire extinguisher, rules for swift removal of rack, etc.


Pontoppidanstraede 109, room 1.103
9220, Aalborg East
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Contact Information

Prioritized staff list

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EU FP7 SmartC2netc: VBN or project home page

PSO-ForskEL RePlan: VBN or project home page

PSO-ForskEL RemoteGrid: VBN or project home page

EU H2020 SUPREME: VBN or project home page

EU H2020 Net2DG: VBN or project home page

PSO-ForskEL Local Heating Concepts for Power Balancing: VBN

MSc Thesis – “Wind Power Plant Control Optimisation with Embedded Application of Wind Turbines and STATCOMs” in collaboration with DONG Wind Power

MSc Thesis – “Advanced Active Power and Frequency Control of Wind Power Plants” in collaboration with Vattenfall

PhD Thesis – “Proof-of-Concept on Next Generation Hybrid Power Plant Control” in collaboration with Vestas Wind Systems

Smart Energy Systems Team

Smart Energy Systems Laboratory

Smart Energy Systems Laboratory