An Adaptive Energy Management Strategy to Extend Battery Lifetime of Solar Powered Wireless Sensor Nodes

Abstract

Traditional energy management strategies of wireless sensor network (WSN) nodes with hybrid energy storage do not adequately combine the merits of supercapacitors (SCs) and batteries, and thus, battery degradation remains a problem that restricts the lifetime of the WSN nodes. In this paper, an adaptive rule-based energy management strategy is proposed to extend the battery lifetime of a solar-powered wireless sensor node. The energy models are constructed with the consideration of the battery degradation, and Poisson distribution is utilized to simulate the power consumption variation of the node. A rule-based energy management strategy that is adaptive with the SC capacity and load conditions is designed. Traditional energy management strategies of the WSN nodes are compared with the proposed one. The simulation results indicate that the proposed strategy can improve the node lifetime from several tens of days to more than ten years. Meanwhile, the strategy ensures the continuous availability of the solar-powered WSN nodes even at night throughout the long lifetime. The robustness of the strategy is also tested. It is revealed that the strategy is adaptive with the SC capacity and workload conditions. The proposed strategy is broadly applicable and promising to resolve the problem of limited battery lifetime for the solar-powered WSN nodes. INDEX TERMS Energy management, hybrid power systems, power system simulation, wireless sensor networks.

Analysis, Modeling and Implementation of a Switching Bi-Directional Buck-Boost Converter Based on Electric Vehicle Hybrid Energy Storage for V2G System

“…In Fig. 23(b), when the shoot-through duty cycle d s is 0.11, the proposed converter steps down the 90V DC-link voltage to 70V Li-battery voltage, which meets the voltage gain given by equation (14). The charging current of the battery remains constant.…”

Minimization of Energy Consumption for Routing in High‐Density Wireless Sensor Networks Based on Adaptive Elite Ant Colony Optimization

“…However, due to the constraints of the sensing environment, in HDWSNs, a lot of nodes only provide restricted energy through batteries. Therefore, effectively cut down the energy consumption of nodes and realize energy-saving routing and data transmission have important research and application value for improving the performance and stability of HDWSNs [4,5].…”

A Multi-Mode Broadband Vibration Energy Harvester Composed of Symmetrically Distributed U-Shaped Cantilever Beams

“…At the same time, the cost of replacing the battery also further restricts the use of these devices. Therefore, the question of how to harvest energy from the surrounding environment to power these devices, instead of simply using batteries, has attracted widespread attention [ 3 , 4 , 5 , 6 ]. There are many forms of energy in the natural environment, such as solar energy, wind energy, vibration energy and thermal energy [ 7 , 8 , 9 , 10 ], and the commonly used energy harvesting mechanisms include photoelectric, piezoelectric [ 11 , 12 ], electromagnetic [ 13 , 14 , 15 ], electrostatic [ 16 ] and triboelectric effects [ 17 , 18 ].…”