Paper Info
Title
Short term power prediction of the photovoltaic power station based on comparison of power profile sequences using F-Score computation
Abstract
Due to the annual increase in energy prices, photovoltaic power stations (PVPS) are often used as a primary source of power for smart off-grid houses. Integration of this kind of energy source is challenging because it is a source of variably generated power due to meteorological uncertainty, but the cost of this energy source rapidly decreases. In this paper, we present results of the short term prediction method of generated power for small PVPS based on self-organizing maps, previously introduced power profiles, their sequences and computing F-Score as an alternative to commonly used algorithms.
Year
DOI
Venue
2014
10.1109/SMC.2014.6974471
Systems, Man and Cybernetics
Keywords
DocType
ISSN
building integrated photovoltaics,prediction theory,pricing,self-adjusting systems,smart power grids,F-score computation,energy prices,energy source cost,meteorological uncertainty,photovoltaic power station,power primary source,power profile sequence comparison,short term power prediction method,small PVPS based on self-organizing maps,smart off-grid houses,variably generated power,photovoltaic power station,power profile,prediction
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Martin Radvanský1115.67
Milos Kudelka211623.81
Václav Snasel31261210.53