Development and comparison of PV production estimation models for mc-Si technologies in Chile and Spain

Photovoltaic power electricity generation nowcasting combining sky camera images and learning supervised algorithms in the Southern Spain

“…In this work, the optimal number of intermediate neurons has been determined empirically as the minimal number of neurons for which estimation performance on a test set is satisfying [13], for more information see Refs. [15,23,55]. [13].…”

“…The algorithm can only find this hyperplane in problems that allow linear separation; in most practical problems, the algorithm maximises the flexible margin by allowing a small number of misclassifications. Thus, the SVM hyperplane equation may be defined as follows [57,58].…”

“…where δ i are the nonnegative Lagrange multiplier of equation ( 2), and K(x, x i ) is a positive-definite kernel function. In general, the determination of an accurate SVM is highly dependent on the optimal choice of parameters for c, ξ and the kernel [57,58].…”

“…Support Vector Machines (SVMs) has proved to be one of the best classifiers for a wide range of situations and is therefore considered one of the benchmarks in the field of statistical learning and machine learning. Its applications in the photovoltaic area have been numerous, many of them also in production prediction of photovoltaic plants [19][20][21][22][23][24][25][26][27][28][29][30]. Among them, the work published by Shi J. et al [30] in 2012, where they developed a one-day-ahead PV power production forecasting model for a single station, based on weather forecast data, real historical power production data and the SVM principle, stands out.…”

A case study of Sunier, a prototypical companyin the evolving green economy

“…Given the relatively novel nature of renewable energies, the main lines of research have opted for comparative analysis of their regulatory systems (4)(5)(6), their degree of efficiency in the use of traditional energy sources (4,(7)(8)(9), their economic impact (7,10,11), their impact on local economies (12,13), or their ecological (14) or landscaping repercussions (13).…”