Fraunhofer-Institut für Angewandte Informationstechnik FIT

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  • Publication
    Structuring the Digital Energy Platform Jungle: Development of a Multi-Layer Taxonomy and Implications for Practice
    ( 2022)
    Duda, Sebastian
    ;
    Bank, Lukas
    ;
    Kaymakci, Can
    ;
    Köberlein, Jana
    ;
    Wenninger, Simon
    ;
    Haubner, Tobias
    ;
    Sauer, Alexander
    ;
    Schilp, Johannes
    Rising and volatile energy prices are forcing production companies to optimize their consumption patterns and reduce carbon emissions to remain competitive. Demand-side management (DSM) or energy flexibility (EF) is a promising option for the active management of electricity demand. With DSM, energy procurement costs can be effectively reduced, for example, by reducing peak loads and taking advantage of volatile energy prices. In addition, renewable energies can be better integrated to reduce carbon emissions while stabilizing the power grid. Although the benefits of DSM for production companies are well known, implementation is not yet widespread. A key barrier is the high requirements of IT systems and the associated effort and complexity involved in setting them up. Companies often lack appropriate IT systems or have historically grown systems that do not allow continuous communication from the machine to the energy market. A variety of different platforms promise solutions to address these challenges. However, when selecting platforms, it is often unclear which aspects and functionalities of a platform are relevant for a company s specific application. To address this gap, we developed a multi-layer taxonomy of digital platforms for energy-related applications in the industry that includes a general, as well as a more specific data-centric and transaction-centric perspective. We develop, revise, and evaluate our taxonomy using insights from literature and analysis of 46 commercially available platforms or platforms developed through research projects. Based on our taxonomy, we derive implications for research and practice. Our results contribute to the descriptive knowledge of digital platforms in energy-related applications. Our taxonomy enables researchers and practitioners to classify such platforms and make informed decisions about their deployment.
  • Publication
    Integrating Energy Flexibility in Production Planning and Control - An Energy Flexibility Data Model-Based Approach
    ( 2021)
    Bank, Lukas
    ;
    Wenninger, Simon
    ;
    Köberlein, Jana
    ;
    Lindner, Martin
    ;
    Kaymakci, Can
    ;
    Weigold, Matthias
    ;
    Sauer, Alexander
    ;
    Schilp, Johannes
    Production companies face the challenge of reducing energy costs and carbon emissions while achieving the logistical objectives at the same time. Active management of electricity demand, also known as Demand Side Management (DSM) or Energy Flexibility (EF), has been recognized as an effective approach to minimize energy procurement costs for example by reducing peak loads. Additionally, it helps to integrate (self-generated, volatile) renewable energies to reduce carbon emissions and has the ability to stabilize the power grid, if the incentives are set appropriately. Although production companies possess great potential for EF, implementation is not yet common. Approaches to practical implementation for integrating energy flexibility into production planning and control (PPC) to dynamically adapt the consumption to the electricity supply are scarce to non-existent due to the high complexity of such approaches. Therefore, this paper presents an approach to integrate EF into PPC. Based on the energy-oriented PPC, the approach identifies and models EF of processes in a generic energy flexibility data model (EFDM) which is subsequently integrated in the energy-oriented production plan and further optimised on the market side. An application-oriented use case in the chemical industry is presented to evaluate the approach. The implementation of the approach shows that EF can have a variety of characteristics in production systems and a clear, structured, and applicable method can help companies to an automated EF. Finally, based on the results of the use case, it is recommended to introduce EF in production companies stepwise by extending existing planning and scheduling systems with the presented approach to achieve a realization of flexibility measures and a reduction of energy costs.