Block diagram of Practical Power-Aware Algorithm for Solar Sensors (PPAASS). The algorithm has four stages. The first predicts the harvested electrical energy based on hi...
Abstract:
Energy-harvesting sensor networks promise unlimited operation throughout time, benefiting ongoing monitoring applications. However, most energy sources, such as sunlight,...Show MoreMetadata
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. Our experimental results showed that PPAASS provided devices with power availability at all times while reducing to a maximum of 15% the time the system did not harvest all the solar energy because the battery was full.
Block diagram of Practical Power-Aware Algorithm for Solar Sensors (PPAASS). The algorithm has four stages. The first predicts the harvested electrical energy based on hi...
Published in: IEEE Access ( Volume: 10)
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- IEEE Keywords
- Index Terms
- Solar Energy ,
- Duty Cycle ,
- Energy Harvesting ,
- Energy Consumption ,
- Photodiode ,
- Season Of The Year ,
- Average Cycle ,
- High Duty ,
- High Duty Cycle ,
- Maximum Capacity ,
- Solar Cells ,
- Time Slot ,
- Previous Day ,
- Mexico City ,
- Solar Panels ,
- Wireless Sensor Networks ,
- Sensor Devices ,
- Power Outages ,
- Set Of Peaks ,
- Battery Energy ,
- Battery Level ,
- End Of Slot ,
- Energy Prediction ,
- Solar Harvesting ,
- Maximum Power Point Tracking ,
- Cycle In Order ,
- Week Of April ,
- Sleep Mode ,
- Energy Harvesting System ,
- Low Duty Cycle
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Solar Energy ,
- Duty Cycle ,
- Energy Harvesting ,
- Energy Consumption ,
- Photodiode ,
- Season Of The Year ,
- Average Cycle ,
- High Duty ,
- High Duty Cycle ,
- Maximum Capacity ,
- Solar Cells ,
- Time Slot ,
- Previous Day ,
- Mexico City ,
- Solar Panels ,
- Wireless Sensor Networks ,
- Sensor Devices ,
- Power Outages ,
- Set Of Peaks ,
- Battery Energy ,
- Battery Level ,
- End Of Slot ,
- Energy Prediction ,
- Solar Harvesting ,
- Maximum Power Point Tracking ,
- Cycle In Order ,
- Week Of April ,
- Sleep Mode ,
- Energy Harvesting System ,
- Low Duty Cycle
- Author Keywords