A Solar Altitude Angle Model for Efficient Solar Energy Predictions.

ABSTRACT: Sunlight is one of the most frequently used ambient energy sources for energy harvesting in wireless sensor networks. Although virtually unlimited, solar radiation experiences significant variations depending on the weather, the season, and the time of day, so solar-powered nodes commonly employ solar prediction models to effectively adapt their energy demands to harvesting dynamics. We present in this paper a novel energy prediction model that makes use of the altitude angle of the sun at different times of day to predict future solar energy availability. Unlike most of the state-of-the-art predictors that use past energy observations to make predictions, our model does not require one to maintain local energy harvesting patterns of past days. Performance evaluation shows that our scheme

SUBMITTER: Herreria-Alonso S 

PROVIDER: S-EPMC7085731 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature