Feasibility of Harvesting Solar Energy for Self-Powered Environmental Wireless Sensor Nodes

Abstract

Energy harvesting has a vital role in building reliable Environmental Wireless Sensor Networks (EWSNs), without needing to replace a discharged battery. Solar energy is one of the main renewable energy sources that can be used to efficiently charge a battery. This paper introduces two solar energy harvesters and their power measurements at different light conditions in order to charge rechargeable AA batteries powering EWSN nodes. The first harvester is a primitive energy harvesting circuit that is built using elementary off-shelf components, while the second harvester is based on a commercial boost converter chip. To prove the effectiveness of harvesting solar energy, five EWSN nodes were distributed at a nature reserve (the Audubon Society of Western Pennsylvania, USA) and the sunlight at their locations was recorded for more than five months. For each recorded illumination, the corresponding harvested energy has been estimated and compared with the average energy consumption of the EWSN with the most power consumption. The results show that the daily harvested energy effectively compensates for the energy consumption of the EWSN nodes, and the battery charge capacity of 295 mAh can reliably support their daily dynamic energy consumption.

Optimizing of Q-Learning Day/Night Energy Strategy for Solar Harvesting Environmental Wireless Sensor Networks Nodes

“…The Q-learning method can be used to control an EWSN node that obtains parameters from the environment and sends data to the Internet via a wireless interface [7]. The system obtains energy for its operation from a solar panel, and in this context, it must optimize its behavior according to the harvested energy [8]. In this experiment, Q-learning will be used to optimize the run/sleep duty cycle to maximize the obtained data.…”

Implementation of Multi-Exit Neural-Network Inferences for an Image-Based Sensing System with Energy Harvesting

“…Electronic sensing systems have been utilized in a variety of applications, including biomedical observation, civil engineering monitoring, and energy resource detection [1][2][3][4][5][6][7][8]. Size of the sensors have reduced to fit into a greater number of applications, and they employ batteries to power themselves without external power connection for easier placement [9][10][11][12][13][14][15][16][17]. As an example, three AAA-sized batteries with an energy capacity of 2400 mAh can continuously power a wireless sensor for 2.4 months [17].…”

“…Size of the sensors have reduced to fit into a greater number of applications, and they employ batteries to power themselves without external power connection for easier placement [9][10][11][12][13][14][15][16][17]. As an example, three AAA-sized batteries with an energy capacity of 2400 mAh can continuously power a wireless sensor for 2.4 months [17]. To maximize system lifetime for a given battery capacity, a sensing system uses a duty-cycled operation between active and sleep modes [14,16].…”

“…The second solution is to develop low-power circuits both for active and sleep modes [18][19][20][21][22][23][24][25]. Lastly, the system includes an energy harvester to recharge the connected battery using environment energy [17]. However, the harvested power is typically lower than power consumption in active mode.…”

“…The system saves energy consumption by 42.54% at 240 MHz clock frequency. A simulation result, based on an exemplary natural outdoor light profile [17] and measured energy consumption of the proposed system, achieves accuracy of 72.1% with an entropy threshold of 1.9 and a battery energy threshold of 1500 J. It requires battery energy of 3.2 kJ, which can be supported by a battery with size of 43 mm × 14 mm × 14 mm [32].…”