Short-Term Prediction of Wave Energy Power Generation Based on SSA-ELM Model
The stochasticity and volatility of wave energy are large,and when point-absorption wave energy generators are applied to wave energy generation,the power output needs to be predicted in advance to ensure the safe and stable operation of the power grid.Therefore,a combined prediction system for wave power generation based on the Sparrow Search Algorithm Optimised Extreme Learning Machine(SSA-ELM)model is proposed.Firstly,the SSA-ELM model is used to make short-term prediction of wave heights based on the meteorological data such as wind direction,wind speed,temperature and barometric pressure.On this basis,a mathematical model of power generation was constructed for the self-reference point absorption wave energy generator.The stability and feasibility of the wave energy power prediction model are verified by analysing the prediction effect of the model.
NETL
NSTL
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