Probabilistic prediction of solar power supply to distribution networks, using forecasts of global horizontal irradiation

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Third Edition

“…Although it is less mature than wind probabilistic forecasting, in recent years the topic of solar probabilistic forecasting has seen a surge in landmark publications Doubleday, Hernandez, and Hodge 2020;Li and Zhang 2020;von Loeper et al 2020;Yang 2019). Unfortunately, noted that the solar forecasting community uses diverse verification tools and sometimes even improper scoring rules for evaluating the quality of the forecasts.…”

Multidimensional Characterisation of Time-dependent Image Data: A Case Study for the Peripheral Nervous System in Ageing Mice

“…Therefore, we use a copula approach (Durante and Sempi, 2010;Joe, 1997) for modelling the joint distribution of axon area and myelin sphericity. Note that the copula approach has demonstrated its benefits in various other applications in order to fit parametric models to multivariate probability distributions, see, e.g., Furat et al (2019a); Neumann et al (2021);von Loeper et al (2020). A short introduction to this topic is given in the following section.…”

Prediction Error and Forecasting Interval Analysis of Decision Trees with an Application in Renewable Energy Supply Forecasting

“…With the increasing penetration of renewable energy, determining the amounts of renewable energy generation is critical to maintain the energy balance and the stability and reliability of power networks. Forecasting the mixing shares of the energy generation offers the guidance of setting up the power generation for each energy source and ensures the load demand of power networks to be satisfied [1,2]. Databased prediction methods, in particular machine learning methods, provide a promising solution to infer the required ratios of energy generation, among which decision tree is a well-recognized approach due to its satisfactory accuracy and interpretation [3][4][5][6].…”

“…Decision tree, compared to other data mining methods, has its own advantages. (1) For casual relationship, it can deal with nonlinear models. In most cases, economics pay more attention to linear models, while if it is a nonlinear model, it will be transferred to be a linear model.…”