Photovoltaic (PV) energy is one of the most promising renewable energies in the world due to its ubiquity and sustainability. However, installation of solar panels on the ground can cause some problems, especially in countries where there is not enough space for installation. As an alternative, floating PV, with advantages in terms of efficiency and environment, has attracted attention, particularly with regard to installing large-scale floating PV for dam lakes and reservoirs in Korea. In this study, the potentiality of floating PV is evaluated, and the power production is estimated for 3401 reservoirs. To select a suitable reservoir for floating PV installation, we constructed and analyzed the water depth database using OpenAPI. We also used the typical meteorological year (TMY) data and topographical information to predict the irradiance distribution. As a result, the annual power production by all possible reservoirs was estimated to be 2932 GWh, and the annual GHG reduction amount was approximately 1,294,450 tons. In particular, Jeollanam-do has many reservoirs and was evaluated as suitable for floating PV installation because of its high solar irradiance. The results can be used to estimate priorities and potentiality as a preliminary analysis for floating PV installation.
The power capacity of solar photovoltaics (PVs) in Korea has grown dramatically in recent years, and an accurate estimation of solar resources is crucial for the efficient management of these solar PV systems. Since the number of solar irradiance measurement sites is insufficient for Korea, satellite images can be useful sources for estimating solar irradiance over a wide area of Korea. In this study, an artificial neural network (ANN) model was constructed to calculate hourly global horizontal solar irradiance (GHI) from Korea Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) images. Solar position variables and five COMS MI channels were used as inputs for the ANN model. The basic ANN model was determined to have a window size of five for the input satellite images and two hidden layers, with 30 nodes on each hidden layer. After these ANN parameters were determined, the temporal and spatial applicability of the ANN model for solar irradiance mapping was validated. The final ANN ensemble model, which calculated the hourly GHI from 10 independent ANN models, exhibited a correlation coefficient (R) of 0.975 and root mean square error (RMSE) of 54.44 W/m² (12.93%), which were better results than for other remote-sensing based works for Korea. Finally, GHI maps for Korea were generated using the final ANN ensemble model. This COMS-based ANN model can contribute to the efficient estimation of solar resources and the improvement of the operational efficiency of solar PV systems for Korea.
A growing number of studies have focused on identifying cognitive processes that are modulated by interoceptive signals, particularly in relation to the respiratory or cardiac cycle. Considering the fundamental role of interoception in bodily self‐consciousness, we here investigated whether interoceptive signals also impact self‐voice perception. We applied an interactive, robotic paradigm associated with somatic passivity (a bodily state characterized by illusory misattribution of self‐generated touches to someone else) to investigate whether somatic passivity impacts self‐voice perception as a function of concurrent interoceptive signals. Participants' breathing and heartbeat signals were recorded while they performed two self‐voice tasks (self‐other voice discrimination and loudness perception) and while simultaneously experiencing two robotic conditions (somatic passivity condition; control condition). Our data reveal that respiration, but not cardiac activity, affects self‐voice perception: participants were better at discriminating self‐voice from another person’s voice during the inspiration phase of the respiration cycle. Moreover, breathing effects were prominent in participants experiencing somatic passivity and a different task with the same stimuli (i.e., judging the loudness and not identity of the voices) was unaffected by breathing. Combining interoception and voice perception with self‐monitoring framework, these data extend findings on breathing‐dependent changes in perception and cognition to self‐related processing.
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