2 results about "Climate change scenario" patented technology

This invention discloses an extreme wind field discrimination method based on non-equilibrium Wasserstein distance, belonging to the field of meteorological wind energy prediction technology. The method includes the following steps: obtaining a set of wind field samples in the study area during the target period to construct a reference field; calculating the non-equilibrium Wasserstein distance between each wind field sample and the reference field as an extremity index; fitting the statistical distribution of the extremity index; calculating an extreme discrimination threshold based on the fitted GEV distribution model; and comparing the extreme index with the extreme discrimination threshold to determine whether the wind field sample is an extreme event or a non-extreme event. This invention, employing the aforementioned extreme wind field discrimination method based on non-equilibrium Wasserstein distance, can provide a high-precision foundation for identifying typical extreme wind fields and constructing scenarios for research such as climate change scenario analysis, extreme scenario risk assessment, renewable energy uncertainty quantification, and energy system resilience optimization.

This invention discloses a method for hydropower prediction under climate change that integrates machine learning, belonging to the field of hydropower data management technology. It includes: simulating the hydropower response under future climate change using a finite number of representative samples in a target region through a physical process-based hydrological-reservoir-hydropower coupling model; constructing a training dataset containing complex nonlinear response characteristics while ensuring the reliability of the model's physical principles and results; then, using machine learning algorithms to establish an efficient generalization model between key climate change features and hydropower generation; finally, applying this model to a larger sample of future climate prediction data covering a wider range of climate change scenarios to achieve rapid and robust hydropower output prediction and uncertainty quantification. This provides more robust and reliable technical support for hydropower prediction under climate change scenarios, as well as for uncertainty quantification and risk decision-making.