A novel MPPT method for autonomous wireless sensor networks node with thermal energy harvesting

Abstract

Energy harvesting is a promising alternative to batteries for autonomous WSN nodes. Although there are various energy harvesting methods using ambient energy sources, this research is focused on thermal energy harvesting because there are abundant thermal sources in industrial sites. As only several mW can be obtained by a thermal energy harvester based on a thermoelectric generator (TEG), improvement of the energy conversion efficiency of the thermal energy harvester is essential. This paper proposes a novel maximum power point tracking (MPPT) method combining coarse adjustment and fine adjustment to enhance the energy conversion efficiency of the harvester. The Direct Adjustment (DA) method for MPPT is adopted in the coarse adjustment stage to avoid disconnecting TEG modules from conversion circuits, while an observation and self-optimization (O&SO) method for MPPT is used in the fine adjustment stage to avoid introducing perturbations and to maintain a stable output power at the maximum power point (MPP). After building up the system simulation model, a series of experiments are conducted to evaluate the proposed MPPT methods. The results show that the DA + O&SO method is an effective MPPT method for a WSN node powered by a TEG. It is able to enhance the regulation speed of the MPPT, improve the continuity of Pout, and avoid the power oscillations around the MPP.