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Open energy services: forecasting and optimization as a service for energy management applications at scale

Wölfle, David; Förderer, Kevin ORCID iD icon 1; Riedel, Tobias; Fernengel, Natascha ORCID iD icon 1; Landwich, Lukas; Mikut, Ralf ORCID iD icon 1; Hagenmeyer, Veit ORCID iD icon 1; Schmeck, Hartmut
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

This article aims at facilitating the widespread application of Energy Management Systems (EMSs), especially in buildings and cities, in order to support the realization of future carbon-neutral energy systems. We claim that economic viability is a severe issue for the utilization of EMSs at scale and that the provisioning of forecasting and optimization algorithms as a service can make a major contribution to achieving it. To this end, we present the Energy Service Generics software framework that allows the derivation of fully functional services from existing forecasting or optimization code with ease. This work documents the strictly systematic development of the framework, beginning with requirement analysis, from which a sophisticated design concept is derived, followed by a description of the implementation of the framework. Furthermore, we present the concept of the Open Energy Services community, our effort to continuously maintain the service framework but also provide ready-to-use forecasting and optimization services. Finally, an evaluation of our framework and community concept, as well as a demarcation between our work and the current state of the art, is presented.


Verlagsausgabe §
DOI: 10.5445/IR/1000183612
Veröffentlicht am 30.07.2025
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2025
Sprache Englisch
Identifikator ISSN: 2632-6736
KITopen-ID: 1000183612
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Erschienen in Data-Centric Engineering
Verlag Cambridge University Press (CUP)
Band 6
Seiten e35
Vorab online veröffentlicht am 14.07.2025
Nachgewiesen in OpenAlex
Dimensions
Scopus
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