The sustainable management of coastal and offshore ecosystems, such as for example coral reef environments, requires an energy efficient collection of accurate data across various temporal and spatial scales. To suitably address the energy supply of marine sensors, in this paper a novel energy harvesting device is proposed, based on a Tubular Permanent MagnetLinear Generator (TPM-LiG). The application is related to the sea wave energy conversion for small sensorized buoy. The optimization process is developed by means of evolutionary computation techniques. The advantage of these algorithms is in the wide exploration of the variables space and in the effective exploitation of the fitness function. The algorithm has been tested on a benchmark case and then applied to the optimization of a power-buoy prototype which has been realized in laboratory with potential significant implications in future marine environment applications.

Optimization of an energy harvesting buoy for coral reef monitoring

PIRISI, ANDREA;GRIMACCIA, FRANCESCO;MUSSETTA, MARCO;ZICH, RICCARDO;
2013-01-01

Abstract

The sustainable management of coastal and offshore ecosystems, such as for example coral reef environments, requires an energy efficient collection of accurate data across various temporal and spatial scales. To suitably address the energy supply of marine sensors, in this paper a novel energy harvesting device is proposed, based on a Tubular Permanent MagnetLinear Generator (TPM-LiG). The application is related to the sea wave energy conversion for small sensorized buoy. The optimization process is developed by means of evolutionary computation techniques. The advantage of these algorithms is in the wide exploration of the variables space and in the effective exploitation of the fitness function. The algorithm has been tested on a benchmark case and then applied to the optimization of a power-buoy prototype which has been realized in laboratory with potential significant implications in future marine environment applications.
2013
2013 IEEE Congress on Evolutionary Computation
9781479904532
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/752614
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