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Topics: Decentralised energy generation, Electricity grids, Operational management & energy management, Load management, Modelling & simulation, Heating & cooling networks
Innovation: The uniform description of any energy conversion systems by the Energy Option Model (EOM) makes it possible to model and discretise the operating states and their energy turnovers. Systems with sector coupling are presented in a practice-led way.
Keywords:
Topics: Decentralised energy generation, Electricity grids, Operational management & energy management, Load management, Modelling & simulation, Heating & cooling networks
Innovation: The uniform description of any energy conversion systems by the Energy Option Model (EOM) makes it possible to model and discretise the operating states and their energy turnovers. Systems with sector coupling are presented in a practice-led way.
Keywords:
Topics: Decentralised energy generation, Electricity grids, Operational management & energy management, Load management, Modelling & simulation, Heating & cooling networks
Innovation: The uniform description of any energy conversion systems by the Energy Option Model (EOM) makes it possible to model and discretise the operating states and their energy turnovers. Systems with sector coupling are presented in a practice-led way.
Keywords:

Quintessence

  • Universal approach to the modelling, flexibilisation and control of hybrid energy conversion systems
  • Development of standardised energy agents that enable manufacturer-independent and cross-sectoral flexibilisation of the energy system
  • Energy agents can be used throughout the lifecycle of an automation solution
  • Agent-based simulation of a real distribution network and field trial

The aim of the research project is to develop a universal approach for modelling, flexibilising and controlling hybrid energy conversion systems. For this purpose, standardised energy agents are being developed which, based on a detailed description of the system behaviour, represent, control and coordinate energy conversion systems in the context of a flexible energy network. This approach is initially being tested in simulations and laboratory environments before being tested in a field trail.

Project context

Managing the flexibility of energy networks by automatically coordinating between the network participants is a key challenge of the energy transition. Existing flexibilisation solutions are usually proprietary. This prevents interoperability and risks the creation of new monopolies. In addition, usually only electric power is considered. In view of the future role of power-to-gas or CHP applications, this isolated approach is insufficient. Instead, electricity, gas and heating networks must be considered together and the transformation processes between these energy sources must be mapped. From the point of view of the project partners, this requires a standardised, open as well as manufacturer-neutral and cross-sectoral approach to flexibilisation. The intention is to realise the approach with agent-based modelling as a – from the practice-based point of view – decentralised, individually centred method.

The Chair of Data Management Systems and Knowledge Representation (DAWIS) at the University of Duisburg-Essen is contributing its expertise to the design and development of multi-agent systems. Previous developments from DAWIS, such as the Agent.GUI simulation tool or the Energy Option Model, provide an important foundation for Agent.HyGrid.

In the Agent.HyGrid project, the Chair of Automation Technology (IfA) at Helmut Schmidt University Hamburg is focussing on modelling systems, designing control algorithms and defining a development process for energy agents.

The Chair of Power System Engineering (EVT) at Bergische Universität Wuppertal has previous experience in the field of network automation. The SAG industrial partner's iNES system, which is to be replicated and extended with agents as part of the Agent.HyGrid project, was co-developed by EVT. In the current project, EVT is responsible among other things for developing algorithms for determining and forecasting network states as well as for clustering the network.

In particular, SAG is applying a business perspective with regard to the system requirements. SAG's iNES system forms the starting point for the developments in the Agent.Hygrid project. In addition, SAG is responsible for selecting suitable hardware for use in the field, providing data from real networks and enabling laboratory and field tests.

Basic energy agent and Energy Option Model (EOM) concept: The agent controls the system based on the model.

Basic energy agent and Energy Option Model (EOM) concept: The agent controls the system based on the model.

© DAWIS / Universität Duisburg-Essen

Research focus

An integral part of Agent.HyGrid is the elaboration of a development process for standardised energy agents which should enable manufacturer-neutral and cross-sectoral flexibility of the energy system. This development process will span the lifecycle of the energy agent – from the design and implementation to simulation studies, lab testing and field deployment. The project will validate this development process using a real distribution network.

Single system models based on the energy option model can be used in different ways. It is thus possible to use them for operational optimisation – for example for use in the day-ahead market – or in the context of real-time control. Since individual systems can be aggregated to any “system of systems”, this will enable the control of power networks, virtual power plants, smart buildings and much more. Based on the Energy Option Model, the energy agent approach developed in Agent.HyGrid allows flexible localisation of the actual control logic so that any decentralisation stages can be realised. Accordingly, an energy agent can be executed centrally or decentrally, and adapted independently of the respective market design.

Deployment scenarios: The engineering process ranges from pure simulation and testbed/laboratory environments to the deployment in real networks.

Deployment scenarios: The engineering process ranges from pure simulation and testbed/laboratory environments to the deployment in real networks.

© DAWIS / Universität Duisburg-Essen

Milestones and successes

In the first step, an agent-based simulation of a real distribution network was developed based on real data from SAG's iNES system – initially based on static time series. In the next step, individual components were equipped with dynamic models and control algorithms. With the integration of a toy windmill as a wind turbine into the simulation, the first step towards a laboratory environment for real systems has already been made. Further steps in this direction will include the integration of real industrial hardware and the control of hardware from the simulation. Finally, the system shall be evaluated in a field trial in a real distribution network.

Application-ready product, tool, software

The approaches developed in Agent.HyGrid are set to be made available to a broader public by the end of 2017. The final product could be made available as an Eclipse project under an open source licence. A final decision, however, is still pending.

Last Update: 15. August 2017

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