| Autor: |
Göran Andersson, Abhishek Rohatgi, Marcus Hildmann |
| Rok vydání: |
2013 |
| Předmět: |
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| Zdroj: |
2013 1st IEEE Conference on Technologies for Sustainability (SusTech). |
| DOI: |
10.1109/sustech.2013.6617293 |
| Popis: |
In this paper, we introduce a constrained Support Vector Machine (SVM) to predict photovoltaic (PV) in-feed. We derive the SVM algorithm with linear constraints and test the method on German PV in-feed with constraints reflecting physical boundaries. We show that the new algorithm shows a significant better performance than a constrained ordinary least squares (OLS) estimator. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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