Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB

Industrial Smart Grids

One of the central issues of mechanical and plant engineering today is to record, monitor and optimize energy consumption. In this process, automation technology plays an essential, indispensable role. It is only automation systems that can collect energy data, match them with process information and intervene as necessary. In 2009, the Automation 2020 paper by the Society for Measurement and Automation Technology (forming part of the Association of German Engineers/Association for Electrical, Electronic & Information Technologies, VDI/VDE) entitled “Significance and Development of Automation by the Year 2020” pointed out to the first and foremost challenge for future automation technology: “Climate change and the increasing shortage of raw materials call for the efficient use of resources and energy. To this end, automation is indispensable.”

Deployment scenarios relevant both in economic and scientific terms could be implemented
if the automation systems and/or the planning and engineering tools had access to energy information. If automation was aware of the typical power consumption rate of specific equipment or manufacturing orders, the system could detect process deviations and thus anomalies. These anomalies frequently indicate wear and tear or poor equipment configuration. In this context, the latter may also mean an economically suboptimal configuration.

This kind of Industrial Smart Grid ensures both more consistent energy consumption by means of active load management in process real-time and an improvement in the network quality by reducing harmonics. In addition to reducing energy costs, this also extends the life cycle of electronic shop-floor equipment.

In this respect, IOSB can support you by providing the following services:

 

 

  • energy data acquisition in interconnected automation systems by means of data loggers and specific energy meters: energy data such as power or harmonics have to be integrated with classical automation data such as sensor values and control or
    ERP system information, e. g. within the framework of a database. To this
    end, the appropriate sensor technology has to be in place. In addition, this
    data has to be transmitted to automation technology on the basis of network
    protocols.
  • energy modeling: a model is required that covers the inter-relationships between
    energy and automation data (equipment data on the field and control levels, order/formula data on the control level and business data on the ERP level).
    The model has to be capable of projecting metrics such as energy consumption
    including the business-related key performance indicators that depend on those
    metrics. 
  • machine learning from computer models analyzing the typical energy consumption of machinery and equipment
  • methodologies for self-optimizing machinery and equipment
  • IT architecture to save, calculate and evaluate energy data and energy management measures spanning the field and control levels
  • IT security for interlinking automated machinery and equipment and smart grids
  • implemention of IEC 61850 protocols in embedded devices
  • communication profiles for standardized energy data transmission, e. g. ProfiEnergy