139 resultados para Energy Harvesting System
Resumo:
We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.
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This paper proposes a hybrid solar cooking system where the solar energy is transported to the kitchen. The thermal energy source is used to supplement the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. Solar energy is transferred to the kitchen by means of a circulating fluid. Energy collected from sun is maximized by changing the flow rate dynamically. This paper proposes a concept of maximum power point tracking (MPPT) for the solar thermal collector. The diameter of the pipe is selected to optimize the overall energy transfer. Design and sizing of different components of the system are explained. Concept of MPPT is validated with simulation and experimental results. (C) 2010 Elsevier Ltd. All rights reserved.
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In this paper, a method of tracking the peak power in a wind energy conversion system (WECS) is proposed, which is independent of the turbine parameters and air density. The algorithm searches for the peak power by varying the speed in the desired direction. The generator is operated in the speed control mode with the speed reference being dynamically modified in accordance with the magnitude and direction of change of active power. The peak power points in the P-omega curve correspond to dP/domega = 0. This fact is made use of in the optimum point search algorithm. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back pulse-width-modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The turbine characteristics are generated by a dc motor fed from a commercial dc drive. All of the control loops are executed by a single-chip digital signal processor (DSP) controller TMS320F240. Experimental results show that the performance of the control algorithm compares well with the conventional torque control method.
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Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.
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This paper describes a bi-directional switch commutation strategy for a resonant matrix converter loaded with a contactless energy transmission system. Due to the different application compared to classical 3 phase to 3 phase matrix converters supplying induction machines a new investigation of possible commutation principles is necessary. The paper therefore compares the full bridge series-resonant converter with the 3 phase to 2 phase matrix converter. From the commutation of the full bridge series-resonant converter, conditions for the bi-directional switch commutation are derived. One of the main benefits of the derived strategy is the minimization of commutation steps, which is independent from the load current sign.
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Energy Harvesting (EH) nodes, which harvest energy from the environment in order to communicate over a wireless link, promise perpetual operation of a wireless network with battery-powered nodes. In this paper, we address the throughput optimization problem for a rate-adaptive EH node that chooses its rate from a set of discrete rates and adjusts its power depending on its channel gain and battery state. First, we show that the optimal throughput of an EH node is upper bounded by the throughput achievable by a node that is subject only to an average power constraint. We then propose a simple transmission scheme for an EH node that achieves an average throughput close to the upper bound. The scheme's parameters can be made to account for energy overheads such as battery non-idealities and the energy required for sensing and processing. The effect of these overheads on the average throughput is also analytically characterized.
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We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.
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In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.
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Researchers can use bond graph modeling, a tool that takes into account the energy conservation principle, to accurately assess the dynamic behavior of wireless sensor networks on a continuous basis.
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Network life time maximization is becoming an important design goal in wireless sensor networks. Energy harvesting has recently become a preferred choice for achieving this goal as it provides near perpetual operation. We study such a sensor node with an energy harvesting source and compare various architectures by which the harvested energy is used. We find its Shannon capacity when it is transmitting its observations over a fading AWGN channel with perfect/no channel state information provided at the transmitter. We obtain an achievable rate when there are inefficiencies in energy storage and the capacity when energy is spent in activities other than transmission.
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In this paper, we determine packet scheduling policies for efficient power management in Energy Harvesting Sensors (EHS) which have to transmit packets of high and low priorities over a fading channel. We assume that incoming packets are stored in a buffer and the quality of service for a particular type of message is determined by the expected waiting time of packets of that type of message. The sensors are constrained to work with the energy that they garner from the environment. We derive transmit policies which minimize the sum of expected waiting times of the two types of messages, weighted by penalties. First, we show that for schemes with a constant rate of transmission, under a decoupling approximation, a form of truncated channel inversion is optimal. Using this result, we derive optimal solutions that minimize the weighted sum of the waiting times in the different queues.
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In this paper, we study duty cycling and power management in a network of energy harvesting sensor (EHS) nodes. We consider a one-hop network, where K EHS nodes send data to a destination over a wireless fading channel. The goal is to find the optimum duty cycling and power scheduling across the nodes that maximizes the average sum data rate, subject to energy neutrality at each node. We adopt a two-stage approach to simplify the problem. In the inner stage, we solve the problem of optimal duty cycling of the nodes, subject to the short-term power constraint set by the outer stage. The outer stage sets the short-term power constraints on the inner stage to maximize the long-term expected sum data rate, subject to long-term energy neutrality at each node. Albeit suboptimal, our solutions turn out to have a surprisingly simple form: the duty cycle allotted to each node by the inner stage is simply the fractional allotted power of that node relative to the total allotted power. The sum power allotted is a clipped version of the sum harvested power across all the nodes. The average sum throughput thus ultimately depends only on the sum harvested power and its statistics. We illustrate the performance improvement offered by the proposed solution compared to other naive schemes via Monte-Carlo simulations.
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We investigate the thermoelectric (TE) figure-of-merit of a single-layer graphene (SLG) sheet by a physics-based analytical technique. We first develop analytical models of electrical and thermal resistances and the Seebeck coefficient of SLG by considering electron interactions with the in-plane and flexural phonons. Using those models, we show that both the figure-of-merit and the TE efficiency can be substantially increased with the addition of isotope doping as it significantly reduces the phonon-dominated thermal conductivity. In addition, we report that the TE open circuit output voltage and output power depends weakly on the SLG sheet dimensions and sheet concentration in the strongly diffusive regime. Proposed models agree well with the available experimental data and demonstrate the immense potential of graphene for waste-heat recovery application.
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We propose energy harvesting technologies and cooperative relaying techniques to power the devices and improve reliability. We propose schemes to (a) maximize the packet reception ratio (PRR) by cooperation and (b) minimize the average packet delay (APD) by cooperation amongst nodes. Our key result and insight from the testbed implementation is about total data transmitted by each relay. A greedy policy that relays more data under a good harvesting condition turns out to be a sub optimal policy. This is because, energy replenishment is a slow process. The optimal scheme offers a low APD and also improves PRR.