Electricity Generation by Green Energy Sources
S. Poursheikhali
Abstract
In this paper, an energy harvesting assisted wireless network is considered where a source, contrary to the conventional networks, harvests its required energy via two independent energy channels. In addition, we assume a destination terminal, which receives interference signals along with the data transferred ...
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In this paper, an energy harvesting assisted wireless network is considered where a source, contrary to the conventional networks, harvests its required energy via two independent energy channels. In addition, we assume a destination terminal, which receives interference signals along with the data transferred by the source. In this model, the source is considered to scavenge energy from the destination's broadcasted signal and ambient interference signal. We model the energy and data channels via Rayleigh-Racian channel model. Then, the system outage probability is obtained after analyzing the outage probability of energy and data channels. Moreover, another scenario in which the source is assumed to harvest energy from only the destination terminal is investigated. Computer simulations are conducted to evaluate the effectiveness of the proposed approach, and the impacts of different system parameters on the system outage probability are investigated. The results indicate the outperformance of the scenario in which energy harvests via two channels compared to the case where only one energy harvesting channel exists. In addition, the overall system outage highly degrades when outage in energy channels decreases, especially in the first scenario.
M. Mohammadpour; Seyed M. M. Modarres-Gheisari; P. Safarpour; R. Gavagsaz-Ghoachani; M. Zandi
Abstract
Large amplitude inter-well oscillations in bi-stable energy harvesters made them a proper energy harvesting choice due to high energy generation. However, the co-existence of the chaotic attractor in these harvesters could essentially decrease their efficiency. In this paper, an algorithm for detecting ...
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Large amplitude inter-well oscillations in bi-stable energy harvesters made them a proper energy harvesting choice due to high energy generation. However, the co-existence of the chaotic attractor in these harvesters could essentially decrease their efficiency. In this paper, an algorithm for detecting chaos in bi-stable energy harvesters based on a data-gathering algorithm and estimating the largest Lyapunov exponent is investigated. First, a simple model of axially loaded non-linear energy harvesters is derived. This model is derived using the Euler-Bernoulli beam theory and the Assumed Mode method considering the Von-Karman non-linear strain-displacement equation. The harvester's numerical simulation results are used to test the algorithm's efficiency and accuracy in identifying chaotic response. The results showed the algorithm's success in detecting chaos in such systems with minimum possible calculation cost. The effect of noise on the algorithm's performance has been investigated, and the results showed the excellent robustness of the algorithm to noise. It can diagnose the harvester's chaotic or harmonic behavior with noise-contaminated data, with 10 percent noise density. The comparison between this algorithm and Wolf's method showed relatively less computation time, up to 80 percent, to detect chaos with reasonable accuracy.