Abstract

Energy-harvesting sensor networks promise unlimited operation throughout time, benefiting ongoing monitoring applications. However, most energy sources, such as sunlight, vary over time and do not guarantee constant power delivery to a device. In addition, these devices lack a battery with the necessary capacity to store enough energy to operate when harvesting is impossible. Thus, managing energy consumption becomes essential for any device to function correctly. This article proposes PPAASS (Practical Power-Aware Algorithm for Solar Sensors), a novel algorithm that allows devices to change their duty cycle to maximize the use of harvested energy based on the device’s battery backup level and solar irradiance predictions. The algorithm was evaluated through simulations performed in Python and with different solar irradiance conditions depending on the season of the year. PPAASS shows a higher average duty cycle than other algorithms in the literature while maintaining a few changes in the duty cycle, which makes it ideal for constant monitoring applications. Furthermore, the implementation of the algorithm shows that the real-time duty cycle adaptation allows a device to react quickly to energy harvesting prediction failures and take full advantage of all the harvested energy. It will enable the device to avoid running out of power while preventing the battery from recharging up to its maximum capacity so it can always store harvested energy.

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