Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1550727 | Solar Energy | 2017 | 12 Pages |
Abstract
⺠We assess forecasting techniques for PV power production without exogenous inputs. ⺠We test five different methods: Persistent, ARIMA, kNN, ANN and GA optimized ANN. ⺠ANN and ANN optimized models perform better than persistent, kNN and ARIMA. ⺠Forecasting error depends strongly on the season. ⺠GA method efficiently determines ANN inputs and general topology.
Related Topics
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Renewable Energy, Sustainability and the Environment
Authors
Hugo T.C. Pedro, Carlos F.M. Coimbra,