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Plant management

Feedback control has traditionally been applied to the equipment and to the unit level while plant-wide and site-wide interactions have only been addressed on long time scales by stationary optimization. Disturbances, demand variations, and shutdowns are then handled by negotiations or phone calls. Increasingly, however, large plants and sites also are operated dynamically to exploit opportunities for cost saving or more sustainable operation. An example for this is a chemical plant or a steel plant with its own power plant for the generation of electricity and steam. Formerly, the operation of the power plant and the procurement of electricity from the grid followed the production plans that were optimized from the point of view of the production plants.
With the increased volatility of the markets for electricity and a multitude of possible contracts with utility providers, a more agile operation that reacts to the situation on the electricity supply side can save cost. In addition, the production can be made more sustainable by using electricity when there is a surplus of supply from renewables and reducing the demand in other periods.
When plants and sites are operated more dynamically, the different units have to be coordinated with respect to the use of internal resources for which no significant storages are available. In theory, with the available optimization technology, plant-wide optimization would be possible, however the lack of models in a uniform formulation, issues of missing information, and the autonomy of the different business units favor distributed solutions that build upon local optimization solutions. The EU-funded project DYMASOS addresses this challenge. In the future, we will extend this work in the context of the European ITN PRONTO in the direction of combined energy and production management.


Hadera, H., Harjunkoski, I., Sand, G., Grossmann, I., Engell, S.: Optimization of steel production scheduling with complex time-sensitive electricity cost. Com-put. Chem. Eng., 76, 2015, 117–136.

European roadmap on research and innovation in engineering and management of cyber-physical systems of systems (CPSoS)

DYN_brochure_CPSoSCyber-physical systems of systems (CPSoS) are large physical systems, such as railway systems, production sites, or the electric grid, that consist of many interacting physical elements and of distributed IT systems for monitoring, control, optimization, and interaction with human operators. These systems are of crucial importance for Europe as they represent some of the most important infrastructures and are the backbone of the European economy.
The dyn group is leading the EU-funded Support Action CPSoS. The goal of CPSoS is to develop a European research and innovation roadmap on cyber-physical systems of systems. CPSoS has collected inputs from a large number of experts, by discussions with the members of its three working groups on transportation and logistics, physically connected CPS, and tools and methods for engineering and management, and by many interviews with domain experts, in particular from industry. In its initial roadmap document, the CPSoS project has identified three key research and innovation challenges:
The first challenge, distributed, reliable and efficient management of cyber-physical systems of systems, results from the fact that control and management of CPSoS cannot be performed in a centralized or hierarchical top-down manner with one authority tightly controlling all subsystems. The second challenge addresses the engineering support for the design-operation continuum of cyber-physical systems of systems. The third challenge is the long-term goal to develop cognitive cyber-physical systems of systems in which big data and cognitive technologies support the users, system operators and managers in complexity management and systems operation.

Cyber-Physical Systems of Systems: Research and Innovation Priorities, Initial Roadmap Document, available at: http://www.cpsos.eu/roadmap/.

Dynamic management of physically coupled systems of systems (DYMASOS)

DYN_brochure_S15_1DYMASOS is a European project that is funded under the 7th Framework Programme in the area of Information and Communication Technology. It addresses the distributed management of systems of systems that are connected by flows of energy and material (cyber-physical systems of systems). Examples of such systems are chemical plants with many units that are coupled by flows of material and energy, e.g. via steam and gas networks and intermediates, or electric grids and electric vehicle charging systems. These systems are managed locally but should be operated such that the overall efficiency is as high as possible while the goals of the local systems (production plans of different business units or the interests of the users of electric cars to find their cars fully charged when they return to the charging stations) are achieved.
In DYMASOS, different techniques for control and optimization of such systems are investigated. The dyn group works on market-based algorithms for the coordination of large chemical plants. The idea of market-based algorithms is that the units are controlled by local optimization algorithms in which the resources, which are constrained and exchanged, are penalized with certain prices. By an iterative adaptation of the prices, which is driven by the imbalance of the networks, the local optimizers are steered towards the plant-wide optimum.
The benefits of this approach are that the scheme is more robust to missing local information or to the switching off of local optimizers than a centralized solution, and that the cost functions and the goals of the local systems do not have to be shared with others.


Paulen, R., Engell, S.: DYMASOS – Dynamic Management of Physically Coupled Systems of Systems. In: ERCIM News 97, April 2014, Special theme: Cyber-Physical Systems, 2014, 51–52.

Stojanovski, G., Maxeiner, L.S., Krämer, S., Engell, S.: Real-Time Shared Resource Allocation by Price Coordination in an Integrated Petrochemical Site. In: Proc. European Control Conference, Linz, Austria, 2015.

The DYMASOS simulation and validation framework

Before productive deployment, system of systems (SOS) management algorithms must be tested in simulations with faithful models of the controlled systems to validate the performance, correctness, and safety of the distributed management system. This task is facilitated by the DYMASOS simulation and validation framework that is tailored to large SOS with decentralized management.

The framework is based on the Modelica language for heterogeneous modelling and provides generic interfaces for the connection of models of the physical processes and implementations of distributed management algorithms. This plug-and-play approach eliminates the tedious task of manual model composition and interfacing, and simplifies the deployment of novel management algorithms to industrial automation systems.



Nazari, S., Sonntag, C., Stojanovski, G., Engell, S.: A Modelling, Simulation, and Validation Framework for the Distributed Management of Large-scale Processing Systems. In: Proc. of 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Copenhagen, 2015.

Kampert, D., Nazari, S, Sonntag, C., Epple, U., Engell, S.: A Framework for Simulation, Optimization and Information Management of Physically-Coupled Systems of Systems. In: Proc. of 15th IFAC Symposium on Information Control Problems in Manufacturing (INCOM), Ottawa, 2015.

Real-time monitoring and optimization of resource efficiency

DYN_brochure_MoreOperational decisions in the day-to-day business of production processes have a significant impact on the energy and material efficiency of the plants. Due to plant-wide interactions, the effect of the decisions is often not transparent to plant operators and managers. Currently, resource efficiency and sustainability indicators are only recorded on long time intervals, e.g. business years. The goal of the EU-funded project MORE—Real-time Monitoring and Optimization of Resource Efficiency in Integrated Processing Plants—is to introduce real-time resource efficiency indicators (REI) to monitor the energy and material efficiency of production plants in the process industries in (near) real-time and subsequently to use them in optimization and decision support for operating staff. Trade-offs between energy efficiency, material efficiency and economic success result in a multi-dimensional decision prob-lem that must be efficiently visualized for easy perception by operators and managers.

Realtime resource efficiency indicators (RT-REI)
The MORE project has developed guidelines for the definition and computation of RT-REI. The REI are defined following a gate-to-gate approach based upon an integrated energy and material flow analysis within the boundaries of individual plants. The RT-REI are product- and resource-specific, i.e. different resources and products are taken into account separately, and independent from economic indicators and indicators of the environmental load are included. The indicators are normalized to theoretical or recorded optimal values to provide an efficient comparison of the actual state of the plant with the best possible operation. The indicators can be aggregated over a set of products. For individual process units, e.g. a distillation column, local indicators can be defined to support the operators. RT-REI have also been defined for batch plants and for mixed batch and continuous plants, taking into account the specific characteristics of such processes.

Visualization of resource efficiency indicators
Energy and resource efficiency has many aspects and is influenced by many operational decisions in a complex manner. The information provided by the RT-REI has to be presented to the operators in a transparent and intuitively understandable fashion. The dyn group therefore has developed a dashboard concept for multi-dimensional RT-REI that uses visualization elements that are best suited to highlight the intended relations and are easily comprehensible. To go beyond the possibilities of classical two- or three-dimensional representations, additional attributes as e.g. color, orientation, size, and specialized visualization elements are combined to dashboard solutions that visualize the contributions to the overall resource efficiency and their evolution.

Model-based decision support
DYN_brochure_S16 The first step towards model-based decision support for the plant operators and managers is a tool for simulation-based what-if analysis that visualizes the effect of possible operation strategies. Beyond this, optimization techniques are used to determine optimal operation strategies with respect to resource efficiency under the current external factors imposed on the system. The approach was applied to an evaporator network of the Austrian viscose producer Lenzing AG. Based on the current fouling state of the evaporators, the optimal combination and loads of the evaporators are determined. Similar tools for other plants are currently under development.


Kalliski, M., Krahé, D., Beisheim, B., Krämer, S., Engell, S.: Resource efficiency indicators for real-time monitoring and optimization of integrated chemical production plants. In: Proc. 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Copenhagen, 2015.