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Decision procedure for efficient data acquisition for distinct energy prognosis models

Vorgehen zur effizienten Datenakuise für unterschiedliche Energieprognosemodelle
 
: Süße, Marian; Stoldt, Johannes; Schlegel, Andreas; Putz, Matthias

:

Franke, J.:
Energy Efficiency in Strategy of Sustainable Production III : Selected, Peer Reviewed Papers from the 4th Green Factory Colloquium, 20.-21. September 2017, Augsburg
Durnten-Zurich: TTP, 2017 (Applied mechanics and materials 871)
ISBN: 978-3-0357-1215-5 (Print)
ISBN: 978-3-0357-2215-4 (CD-ROM)
ISBN: 978-3-0357-3215-3 (eBook)
pp.115-124
Green Factory Bavaria Colloquium <4, 2017, Augsburg>
English
Conference Paper
Fraunhofer IWU ()
energy data acquisition; efficiency evaluation; decision support; procedure model

Abstract
The current challenges for enterprises are heavily linked to resource and energy efficiency, a result of political guidelines and the overall consciousness for environmental issues in society. Thus, the impact of energy efficiency on factory planning and production planning is of undeniable importance. Adequate consumption information utilising various depiction methods has become a necessity in this respect. Yet, only few works provide information on the efficiency of energy data acquisition methods. This paper proposes a methodological framework for defining an efficient procedure for energy data acquisition in accordance with the depiction or prognosis method. A preliminary literature review indicates the variety of methods for energy data depiction and prognosis. The classification of these methods regarding planning state and planning levels leads to the estimation of relevant input data. Based on the fundamental investigation of necessary input data the decision approach is developed with a general heuristic decision model and incorporates the Analytic Hierarchy Process for quantification and solution of the overall decision problem. Therefore the integration of multiple decision criteria enables the consideration of different quantitative and qualitative influences. As a result the whole approach supports the collaborative identification of means for energy data acquisition and is applicable in several circumstances where energy data needs to be gathered efficiently. The decision procedures exemplary application has shown the general proficiency of the approach and that excessive data acquisition which contradicts efficiency is avoidable.

: http://publica.fraunhofer.de/documents/N-470098.html