Marine Renewable Energy Reserve Prediction Method Based on DSR Model

Abstract

ABSTRACT Li, Y.; Huang, Y., and Zhang, M., 2019. Marine renewable energy reserve prediction method based on DSR model. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 601–606. Coconut Creek (Florida), ISSN 0749-0208. In order to avoid the waste of the marine renewable energy reserves, the traditional method adopts the linear distribution sequence prediction algorithm, and the random distribution of the reserve distribution sequence of the marine renewable energy is not taken into consideration, leading to a low prediction accuracy. A Dynamic Source Routin (DSR) model-based renewable energy reserve sequence prediction algorithm is proposed. The non-linear distribution sequence analysis model of the marine renewable energy reserve data is constructed, the marine renewable energy reserve data is embedded into the high-phase space by adopting a phase space reconstruction method, the non-linear characteristic of the marine renewable energy reserve distribution sequence is extracted in the phase space. And the accurate prediction of the marine renewable energy reserve distribution sequence is realized, and the accurate prediction of the marine renewable energy reserves is realized by combining the DSR model. The simulation results show that the accuracy of the marine renewable energy reserves prediction is high by the method, and the internal structure characteristics of the marine renewable energy reserve data can be effectively reflected by the DSR model analysis and reconstruction. And the characteristic analysis capability of the prediction performance and the marine renewable energy reserve data is improved.