Among renewable energy sources the sun is certainly one of the easiest to exploit. Solar panels allow generating electrical energy but they generally have low efficiency. It is therefore important to optimize a solar module to maximize its energy production. Faults can have for example a big impact on the amount of energy production, and should be avoided if possible. This goal can be achieved by designing fault tolerant photovoltaic modules. In this paper, we propose a sensing and repair system for photovoltaic modules. The system is based on two key elements: sensing of the photovoltaic cell status through memristors and dynamic reconfiguration of the connections among cells. Using a memristor for sensing allows creating simple yet effective measuring systems that is able to detect the state of each cell of the modules. This information can be read externally or can be used internally by the reconfiguration system. The second key element of our system is indeed a new reconfiguration scheme that allows dynamically changing the connections among cells. This system can be used to reconfigure the connections among cells to maximize energy production, depending on the health state of each solar cell. The same system can be used to substitute redundant cells in the array to compensate faults and to improve energy production. We present a detailed characterization and power analysis of the system, highlighting the improvements in energy production and demonstrating its ability to compensate faults. The solution that we propose is modular and can be extended to arrays of any size. It can also be potentially embedded inside a solar panel, leading to a self-healing device that can improve the energy that is generating.

Gnoli, L., Riente, F., Ottavi, M., Vacca, M. (2021). A memristor-based sensing and repair system for photovoltaic modules. MICROELECTRONICS RELIABILITY, 117, 114026 [10.1016/j.microrel.2020.114026].

A memristor-based sensing and repair system for photovoltaic modules

Ottavi M.;
2021-01-01

Abstract

Among renewable energy sources the sun is certainly one of the easiest to exploit. Solar panels allow generating electrical energy but they generally have low efficiency. It is therefore important to optimize a solar module to maximize its energy production. Faults can have for example a big impact on the amount of energy production, and should be avoided if possible. This goal can be achieved by designing fault tolerant photovoltaic modules. In this paper, we propose a sensing and repair system for photovoltaic modules. The system is based on two key elements: sensing of the photovoltaic cell status through memristors and dynamic reconfiguration of the connections among cells. Using a memristor for sensing allows creating simple yet effective measuring systems that is able to detect the state of each cell of the modules. This information can be read externally or can be used internally by the reconfiguration system. The second key element of our system is indeed a new reconfiguration scheme that allows dynamically changing the connections among cells. This system can be used to reconfigure the connections among cells to maximize energy production, depending on the health state of each solar cell. The same system can be used to substitute redundant cells in the array to compensate faults and to improve energy production. We present a detailed characterization and power analysis of the system, highlighting the improvements in energy production and demonstrating its ability to compensate faults. The solution that we propose is modular and can be extended to arrays of any size. It can also be potentially embedded inside a solar panel, leading to a self-healing device that can improve the energy that is generating.
2021
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/01 - ELETTRONICA
English
Photovoltaic array
Memristor
Reconfigurable architecture
Gnoli, L., Riente, F., Ottavi, M., Vacca, M. (2021). A memristor-based sensing and repair system for photovoltaic modules. MICROELECTRONICS RELIABILITY, 117, 114026 [10.1016/j.microrel.2020.114026].
Gnoli, L; Riente, F; Ottavi, M; Vacca, M
Articolo su rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/291017
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