Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks

• Published in: IEEE transactions on industrial electronics (1982) Vol. 55; no. 7; pp. 2759 - 2766
• Main Authors: Dondi, D., Bertacchini, A., Brunelli, D., Larcher, L., Benini, L.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-07-2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Circuits; Design engineering; Efficiency; Energy harvesting; Harvesters; Mathematical models; Maximum power point tracking (MPPT); Methodology; modeling and optimization; Networks; Optimization; Optimization methods; Panels; Parameter extraction; Photovoltaic systems; Power system modeling; Predictive models; PSpice simulations; Sensors; Solar energy; solar harvester; Solar power generation; Studies; Wireless sensor networks; Modelling and Optimization; MPPT Maximum Power Point Tracking; PSpice Simulations; Solar harvester
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2008.924449

In this paper, we propose a methodology for optimizing a solar harvester with maximum power point tracking for self-powered wireless sensor network (WSN) nodes. We focus on maximizing the harvester's efficiency in transferring energy from the solar panel to the energy storing device. A photovoltaic panel analytical model, based on a simplified parameter extraction procedure, is adopted. This model predicts the instantaneous power collected by the panel helping the harvester design and optimization procedure. Moreover, a detailed modeling of the harvester is proposed to understand basic harvester behavior and optimize the circuit. Experimental results based on the presented design guidelines demonstrate the effectiveness of the adopted methodology. This design procedure helps in boosting efficiency, allowing to reach a maximum efficiency of 85% with discrete components. The application field of this circuit is not limited to self-powered WSN nodes; it can easily be extended in embedded portable applications to extend the battery life.