Applied energy sources demands of hypothetical manufacturing companies

Published: 6 July 2021| Version 2 | DOI: 10.17632/y98fwg264s.2
Christian Gahm


Because the sustainable development of a society is strongly related to the sustainable development of its manufacturing companies, more and more of the companies decide to install and operate on-site energy conversion (utility) systems (ECS). In consequence, many approaches for the design and operation of ECSs are developed. The provided data set contains the applied energy sources demand of different hypothetical manufacturing companies to make different approaches for the design and operation comparable. Altogether 32 company types (all having a production system with parallel machines) are considered and distinguished according to the following production-related parameters: production system size (i.e., number of machines), job size (i.e., mean processing times) and variability (i.e., processing time distribution), energy demand type (i.e., energy demand course), and energy demand variability (i.e., energy demand distribution). For each company type, we provide the energy demands of 240 production days. In addition, the energy demand data is generated with respect to two scheduling objectives: makespan and total flow time. Thus, a total of 15,360 energy demand time series (32 company types, 2 scheduling objectives, and 240 production days) is available. The data consist of three parts: First part lists the planning horizons (lengths) of the time series for each production day. The second part contains the raw data of the energy demands (one time series per company type and scheduling objective). The third part contains the aggregated values (10 minutes aggregated to one period). Note that the combination of part one and two enables the separation of the data of an individual production day. Further detail about the data can be found in “A flexible approach for the dimensioning of on-site energy conversion systems for manufacturing companies”.



Engineering, Operations Research, Energy Application