Institut für Wirtschaftsinformatik

Dauerhafte URI für die Sammlunghttps://irf.fhnw.ch/handle/11654/66

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Autor:in: search.filters.author.Helfert, MarkusHochschule: search.filters.hochschule.Hochschule für Wirtschaft

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    Publikation
    Cloud service quality model: a cloud service quality model based on customer and provider perceptions for cloud service mediation
    (2019) Giovanoli, Claudio; Méndez Muñoz, Victor; Ferguson, Donald; Helfert, Markus; Pahl, Claus
    The field of cloud service selection tries to support customers in selecting cloud services based on QoS attributes. For considering the right, QoS attributes it is necessary to respect the customers and the providers’ perception. This can be made through a Service Quality Model. Thus, this paper introduces a Cloud Service Quality Model based on a Systematic Literature Review and user interviews as well as providers perceptions.
    04B - Beitrag Konferenzschrift
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    Publikation
    Technical Validation of the RLS Smart Grid Approach to increase Power Grid Capacity without Physical Grid Expansion
    (SciTePress, 05/2019) Christen, Ramón; Layec, Vincent; Wilke, Gwendolin; Wache, Holger; Donnellan, Brian; Klein, Cornel; Helfert, Markus
    The electrification of the global energy system and the shift towards distributed power production from sus- tainable sources triggers an increased network capacity demand at times of high production or consumption. Existing energy management solutions can help mitigate resulting high costs of large-scale physical grid rein- forcement, but often interfere in customer processes or restrict free access to the energy market. In a preceding paper, we proposed the RLS regional load shaping approach as a novel business model and load management solution in middle voltage grid to resolve this dilemma: market-based incentives for all stakeholders are pro- vided to allow for flexible loads that are non-critical in customer processes to be allocated to the unused grid capacity traditionally reserved for N-1 security of supply. We provide a validation of the technical aspects of the approach, with an evaluation of the day-ahead load forecasting method for industry customers and a load optimization heuristics. The latter is tested by a simulation run on a scenario of network branch with provoked capacity bottlenecks. The method handles all provoked critical network capacity situations as expected.
    04B - Beitrag Konferenzschrift