Analysis of Photovoltaic Energy Using Kernel Smoothing

HOROVÁ, Ivanka a Jan KOLÁČEK. Analysis of Photovoltaic Energy Using Kernel Smoothing. In The 25th Annual TIES Conference. 2015.

Základní údaje

• Originální název: Analysis of Photovoltaic Energy Using Kernel Smoothing
• Autoři: HOROVÁ, Ivanka a Jan KOLÁČEK.
• Vydání: The 25th Annual TIES Conference, 2015.

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Prezentace na konferencích
• Obor: 10101 Pure mathematics
• Stát vydavatele: Spojené arabské emiráty
• Utajení: není předmětem státního či obchodního tajemství
• Organizační jednotka: Přírodovědecká fakulta
• Klíčová slova anglicky: multivariate kernel regression; bandwidth matrix; kernel smoothing
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

The share of power generated by the solar plant is constantly increasing, despite the unreliable character of this type of energy. In order to ensure the optimal utilization of the generated power, its forecasting becomes more and more important. The crucial issue is to determine the relationship between weather characteristics, mainly solar radiation and temperature, and the photovoltaic energy. We propose to use a multivariate kernel regression for this task. Methods of kernel estimations represent one of the most effective smoothing techniques. These methods are simply to understand and they possess good statistical properties. The most important factor in the multivariate kernel regression is a bandwidth matrix. This matrix controls both the amount and the direction of the multivariate smoothing. Considerable attention is paid to constrained parametrization of the bandwidth matrix such as a diagonal matrix.We propose a method based on an optimally balanced relation between the integrated variance and the integrated squared bias. This method is also suitable for a gradient estimation, i.e., it is able to detect „gaps“ and „holes“ of the regression surface. In the present contribution the method is applied on data consisting of hourly values of energy generated by solar power plants in a specific area and of predictions of solar radiation and temperature provided by numerical prediction model ALADIN.

Návaznosti

• GA15-06991S, projekt VaV: Název: Analýza funkcionálních dat a související témata

Investor: Grantová agentura ČR, Analýza funkcionálních dat a související témata