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An N-state Markov-chain mixture distribution model of the clear-sky index
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group)ORCID iD: 0000-0003-0051-4098
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (BEESG)ORCID iD: 0000-0003-4887-9547
2018 (English)In: Solar Energy, ISSN 0038-092X, E-ISSN 1471-1257, Vol. 173, p. 487-495Article in journal (Refereed) Published
Abstract [en]

This paper presents an N-state Markov-chain mixture distribution approach to model the clear-sky index. The model is based on dividing the clear-sky index data into bins of magnitude and determining probabilities for transitions between bins. These transition probabilities are then used to define a Markov-chain, which in turn is connected to a mixture distribution of uniform distributions. When trained on measured data, this model is used to generate synthetic data as output. The model is an N-state generalization of a previously published two-state Markov-chain mixture distribution model applied to the clear-sky index. The model is tested on clear-sky index data sets for two different climatic regions: Norrköping, Sweden, and Oahu, Hawaii, USA. The model is also compared with the two-state model and a copula model for generating synthetic clear-sky index time-series as well as other existing clear-sky index generators in the literature. Results show that the N-state model is generally on par with, or superior to, state-of-the-art synthetic clear-sky index generators in terms of Kolmogorov–Smirnov test statistic, autocorrelation and computational speed.

Place, publisher, year, edition, pages
2018. Vol. 173, p. 487-495
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-363525DOI: 10.1016/j.solener.2018.07.056ISI: 000452940800047OAI: oai:DiVA.org:uu-363525DiVA, id: diva2:1256947
Available from: 2018-10-18 Created: 2018-10-18 Last updated: 2019-01-16Bibliographically approved

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Munkhammar, JoakimWidén, Joakim

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