Cloud Computing Design Patterns for MLOps: Applications to Virtual Power Plants

Rakshith Subramanya, Paula Räisänen, Seppo Sierla, Valeriy Vyatkin

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

51 Lataukset (Pure)

Abstrakti

Virtual Power Plants (VPPs) are a key factor in smart grids, and they use cloud computing to integrate and manage Distributed Energy Resources (DERs). VPPs use Machine Learning (ML) methods to optimize various tasks. Machine Learning Operations (MLOps) methodology is a set of techniques that targets to develop, deploy and maintain ML applications smoothly on production. Cloud design patterns (CDPs) are general reusable solutions for common cloud problems that can improve the reliability, scalability, and quality of cloud applications. This paper discusses how CDPs can help in building complex ML applications on cloud with MLOps practices which can help VPPs to optimize their workloads. The paper also provides an example implementation on a public cloud provider.

AlkuperäiskieliEnglanti
OtsikkoIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
KustantajaIEEE
Sivumäärä7
ISBN (elektroninen)979-8-3503-3182-0
DOI - pysyväislinkit
TilaJulkaistu - 2023
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaAnnual Conference of the IEEE Industrial Electronics Society - Singapore, Singapore, Singapore, Singapore
Kesto: 16 lokak. 202319 lokak. 2023
Konferenssinumero: 49

Julkaisusarja

NimiIECON Proceedings (Industrial Electronics Conference)
ISSN (painettu)2162-4704
ISSN (elektroninen)2577-1647

Conference

ConferenceAnnual Conference of the IEEE Industrial Electronics Society
LyhennettäIECON
Maa/AlueSingapore
KaupunkiSingapore
Ajanjakso16/10/202319/10/2023

Sormenjälki

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    Sierla, S., Räisänen, P., Subramanya, R., Hosaagrahara Srinivas, N. & Hölttä, T.

    01/06/202231/12/2023

    Projekti: Business Finland: New business from research ideas (TUTLI)

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