Abstract
In this work we describe a systematic approach to power subsystem capacity planning for solar energy harvesting embedded systems, such that uninterrupted, long-term (i.e., multiple years) operation at a predefined performance level may be achieved. We propose a power subsystem capacity planning algorithm based on a modified astronomical model to approximate the harvestable energy and compute the required battery capacity for a given load and harvesting setup. The energy availability model takes as input the deployment site’s latitude, the panel orientation and inclination angles, and an indication of expected meteorological and environmental conditions.We validate the model’s ability to predict the harvestable energy with power measurements of a solar panel. Through simulation with 10 years of solar traces from three different geographical locations and four harvesting setups, we demonstrate that our approach achieves 100% availability at up to 53% smaller batteries when compared to the state-of-the-art.
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Buchli, B., Sutton, F., Beutel, J., Thiele, L. (2014). Towards Enabling Uninterrupted Long-Term Operation of Solar Energy Harvesting Embedded Systems. In: Krishnamachari, B., Murphy, A.L., Trigoni, N. (eds) Wireless Sensor Networks. EWSN 2014. Lecture Notes in Computer Science, vol 8354. Springer, Cham. https://doi.org/10.1007/978-3-319-04651-8_5
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DOI: https://doi.org/10.1007/978-3-319-04651-8_5
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