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Single and multiple step forecasting of solar power production: applying and evaluating potential models
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The aim of this thesis is to apply and evaluate potential forecasting models for solar power production, based on data from a photovoltaic facility in Sala, Sweden. The thesis evaluates single step forecasting models as well as multiple step forecasting models, where the three compared models for single step forecasting are persistence, autoregressive integrated moving average (ARIMA) and ARIMAX. ARIMAX is an ARIMA model that also takes exogenous predictors in consideration. In this thesis the evaluated exogenous predictor is wind speed. The two compared multiple step models are multiple step persistence and the Gaussian process (GP). Root mean squared error (RMSE) is used as the measurement of evaluation and thus determining the accuracy of the models. Results show that the ARIMAX models performed most accurate in every simulation of the single step models implementation, which implies that adding the exogenous predictor wind speed increases the accuracy. However, the accuracy only increased by 0.04% at most, which is determined as a minimal amount. Moreover, the results show that the GP model was 3% more accurate than the multiple step persistence; however, the GP model could be further developed by adding more training data or exogenous variables to the model.

Place, publisher, year, edition, pages
2019. , p. 20
Series
TVE-STS ; 19002
Keywords [en]
Forecasting, Gaussian process, ARIMA, ARIMAX, Solar power production
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:uu:diva-384340OAI: oai:DiVA.org:uu-384340DiVA, id: diva2:1320173
External cooperation
Sun Labs Nordic
Educational program
Systems in Technology and Society Programme
Supervisors
Examiners
Available from: 2019-06-12 Created: 2019-06-04 Last updated: 2019-06-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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