Approaches for Generating Synthetic Industrial Load Profiles in Greenfield Energy System Planning

Greenfield factory planning projects have to deal with uncertainties in the initial planning stages resulting in a poor economic and ecological target attainment. Due to the lack of time-dependent data, initial planning stages are usually based on static values. This primarily affects energy and technical building system planning since the system components size is primarily based on peak load demands. As a result, oversized system components are planned with higher capital costs and inefficient operating states, resulting in higher operational costs and environmental impact. Synthetic load profiles represent a possible solution to deal with the unavailability of measured data in greenfield factory planning. This paper evaluates the state of the art concerning the generation of synthetic load profiles for manufacturing cells. On the one hand, it was found that estimating the time-dependent energy demand in industry is usually based on measured load profile data for load forecasting or prediction. On the other hand, approaches for residential systems achieve results without measured load profile data. Nevertheless, residential systems are not within the scope of industrial systems. An approach for generating industrial load profiles in greenfield energy system planning is missing.