Abstract
Accurate forecasts of ocean waves energy can not only reduce costs for investment, but it is also essential for the management and operation of electrical power. This paper presents an innovative approach based on long short-term memory (LSTM) to predict the power generation of an economical wave energy converter named “Searaser”. The data for analysis is provided by collecting the experimental data from another study and the exerted data from a numerical simulation of Searaser. The simulation is performed with Flow-3D software, which has high capability in analyzing fluid–solid interactions. The lack of relation between wind speed and output power in previous studies needs to be investigated in this field. Therefore, in this study, wind speed and output power are related with an LSTM method. Moreover, it can be inferred that the LSTM network is able to predict power in terms of height more accurately and faster than the numerical solution in a field of predicting. The network output figures show a great agreement, and the root mean square is 0.49 in the mean value related to the accuracy of the LSTM method. Furthermore, the mathematical relation between the generated power and wave height was introduced by curve fitting of the power function to the result of the LSTM method.
Highlights
Fossil fuels are still the most essential source of energy in the world [1]
For putational fluid dynamic and numerically solving the governing equations, a relationship between wave height and output power was found, and the experimental data of He’s between study [24] demonstrate the relation between wind flow speed and wave height, which is shown as as Figure. By collecting collecting these these data, data, we we can can reach reach the the main main goal goal of of this this research, research, shown which is to find a relationship between wind speed and output power
This section describes the results of the evaluation of the wave power generation preht
Summary
Fossil fuels are still the most essential source of energy in the world [1]. Such nonrenewable energy sources significantly contribute to environmental pollution and climate change [2]. Finding alternative energy resources with less carbon footprint is of significant importance. Recently developing non-petroleum-based energy resources has increased tremendously. Among the different sources of renewable energies, solar, wind, tidal and geothermal energies are the most well-known ones [3]. Ocean wave energy has the second largest potential among all ocean renewable energy sources [4]
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