Short-term prediction of power fluctuations in photovoltaic systems using chaos theory

This paper proposes a novel short-term prediction method for power fluctuations in a photovoltaic (PV) system based on chaos theory. A data vector composed of n data points is embedded in an n-dimensional vector space by Takens´ embedding theorem. The time delay is determined at 300 s by autocorrelation analysis, and the embedding dimension is determined to be 5 by the Grassberger-Procaccia algorithm. Next, the PV power in the near feature is predicted by using the local fuzzy reconstruction method. A simulation of the smoothing control of power in a PV system with an energy storage device consisting of electric double layer capacitors (EDLCs) is carried out. The largest reduction in the EDLCs´ capacity is 3.81 kJ, which can be achieved on a clear day.