Large Scale Energy Harvesting and Transfer Networks
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초록
Allowing wireless networks to harvest energy from renewable sources provides a solution for rapidly growing energy consumption by the networks. However, the temporal and spatial variations of the energy field can lead to fluctuations in power supplied to the network and thereby degrade the network performance. This has motivated recent research on modeling large scale energy harvesting networks and quantifying the effects of energy randomness on network performance. This paper reviews a series of recent works that apply stochastic geometry as the primary tool to model and analyze such networks and shows that this branch of mathematics provides a power and versatile tool for designing large scale energy harvesting networks. Furthermore, the paper presents the new concept of connecting the networks to the grid for supplying residual harvested energy to the grid and quantifies the expected amount.
Abstract
Allowing wireless networks to harvest energy from renewable sources provides a solution for rapidly growing energy consumption by the networks. However, the temporal and spatial variations of the energy field can lead to fluctuations in power supplied to the network and thereby degrade the network performance. This has motivated recent research on modeling large scale energy harvesting networks and quantifying the effects of energy randomness on network performance. This paper reviews a series of recent works that apply stochastic geometry as the primary tool to model and analyze such networks and shows that this branch of mathematics provides a power and versatile tool for designing large scale energy harvesting networks. Furthermore, the paper presents the new concept of connecting the networks to the grid for supplying residual harvested energy to the grid and quantifies the expected amount.
참고문헌 (19)
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