The introduction of new technologies and processes, particularly the adoption of renewable energy sources, brings increased volatility into the dynamic relationship between manufacturing industries and their counterparts in the energy markets. To address this challenge, industrial energy research is dedicated to bringing forth dynamic, holistic and more straightforward solutions. One of these solutions involves the development of load and generation profiles, which allows for a detailed examination of how individual industries consume and generate energy over time. These valuable insights enhance the collaboration among key stakeholders, including grid operators, energy suppliers, and industrial players. As a result, it significantly improves decision-making processes, fostering advancements in the industrial sector.
Throughout an extensive literature research, it can be concluded that a holistic solution on synthetic load and generation profiles in industry has not been developed yet. State-of-the-art works either rely on vast amounts of data or focus solely on selected applications such as generating electricity load profiles for specific industrial subsectors. Recognizing this research gap, this thesis presents novel developments for generating load (and generation) profiles (LPs) and waste heat profiles (WHPs) of the entire industrial sector encapsulated in an all-in-one software solution named “Ganymed”.

Overall, the industrial sector is divided into energy-intensive and non-energy-intensive subsectors. As the energy-intensive subsectors exhibit a limited product and process variety, a bottom-up methodology starting with data on the process level is applied. Throughout the enhancement of the simulation method of discrete event simulation, these processes can be accumulated to whole production routes, which offers the basis for generating LPs and WHPs for energy-intensive subsectors. It can be stated that processes must contain data on energy-relevant and time-resolved properties to achieve LP and WHP generation. Here, the most energy-intensive processes influence the resulting LPs and WHPs of individual industries to the greatest extent. Especially batch-operated processes make up for main shares in peak loads. Non-energy-intensive subsectors exhibit more complex production routes, deeming a top-down approach to be the more suitable methodology for depicting them. Various industrial databases form the basis for novel findings within these energy system analyses, which are further deployed to generate LPs and WHPs for these subsectors. For example, this thesis uncovers subsector-specific “economy of scale” effects for industrial energy systems, correlations of shift models and deployed employees at the plant, calculations for maximum outlet temperatures of industrial waste heat etc.
Both methodological approaches are embedded into the software environment “Ganymed”, being the first-of-its-kind of software for generating synthetic LPs and WHPs of the industry.