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With the significant increase in the amount of solar energy sources, the variation in the production caused by the stochastic nature of these sources becomes a larger problem for the electrical grid. Having a large percentage of installed units, therefore, requires some type of both short- and long-term planning of energy production. Most planning and forecasting tools require a large amount of solar energy data for the location in question and oftentimes that data is difficult to obtain. In this paper, we propose a method for generating synthetic solar irradiance data and test its applicability on forecasting and long-term planning problems. Synthetic data are generated using various generative adversarial networks and masked autoencoder based models, which are all trained on a dataset of solar irradiance data measured on the territory of the city of Banja Luka in Bosnia and Herzegovina. The synthetic data are evaluated both on different types of short-term forecasting tools and a long-term solar plant simulation tool, and the obtained results are compared with the cases where real data is used. By comparing the results, we have concluded that by using generative models we are able to generate synthetic data which is not only realistic, but applicable for both of these uses. [ABSTRACT FROM AUTHOR]

Background/Aim. In the past two decades, we have witnessed the emergence of new radiation therapy techniques, radiotherapy treatment planning system (TPS) with calculating algorithms for the dosage calculation in a patient, units for multislice computed tomography (CT) and image-guided treatment delivery. The aim of the study was investigating the significant difference in dosimetric calculation of radiotherapy TPS in relation to the values obtained by measuring on the linear accelerator (LINAC), and the accuracy of dosimetric calculation between calculating algorithms Analytical Anisotropic Algorithm (AAA) and Acuros XB in various tissues and photon beam energies. Methods. For End-to-End test we used the heterogeneous phantom CIRS Thorax002LFC, which anatomically represents human torso with a set of inserts known as relative electron densities (RED) for obtaining a CT calibration curve, comparable to the "reference" CIRS 062M phantom. For the AAA and Acuros XB algorithms and for 6 MV and 16 MV photon beams in the TPS Varian Eclipse 13.6, four 3D conformal (3DCRT), and one intensity modulated (IMRT) and volumetric modulated arc (VMAT) radiotherapy plans were made. Measurements of the absolute dose in Thorax phantom, by PTW-Semiflex ionization chamber, were carried out on three Varian-DHX LINACs. Results. The difference between "reference" and measured CT conversion curves in the bone area was 3%. For 476 phantom measurements, the difference between measured and TPS calculated dose of 3-6%, was found in 30 (6.3%) c ases. According to regression analysis, the standardized Beta coefficient for relative errors, 6 MV vs. 16 MV, was 0.337 (33.7%, p < 0.001). Mean relative errors for AAA and Acuros XB, using Mann-Whitney test, for bones were 1.56% and 2.64%, respectively (p = 0.004). Conclusion. End-to-End test on Thorax002LFC phantom proved the accuracy of TPS dose calculation in relation to the one delivered to a patient by LINAC. There was a significant difference for photon energies relative errors (higher values are obtained for 16 MV vs. 6 MV). A statistically significant minor relative error in AAA vs. Acuros XB was found for the bone. [ABSTRACT FROM AUTHOR]