Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks
By D. Dondi, A. Bertacchini, Davide Brunelli, Luca Larcher, Luca Benini. IEEE transactions on industrial electronics (1982. Print), 2008
371 citations recorded by the source corpus.
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.
Subfields: Electrical and Electronic Engineering, Mechanical Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/1063a861f7d922fe534bc8816bac1e9d22f1f77f
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Citations in the corpus
- Energy-Harvesting Wireless Sensor Networks (EH-WSNs) (2018, background): “A key design consideration with respect to solar energy harvesters, is Maximum Power Point Tracking (MPPT) (Rodriguez and Amaratunga 2007; Simjee and Chou 2008; Dondi et al. 2008; ACM Transactions on Sensor Networks, Vol. 14, No. 2, Article 10.”
- EAACK—A Secure Intrusion-Detection System for MANETs (2013, neutral): “been devoted to such research topic [1]–[3], [6]–[9], [15], [16], [22], [24], [26], [29]–[31].”