Energy Harvesting Scenarios Research Articles

A model for the triboelectric nanogenerator with inductive load and its energy boost potential

A new method which exploits energy oscillation between the TENG and an inductive load is proposed to boost the energy output for the triboelectric nanogenerator (TENG) with contact-separation (CS) mode. A time-domain theoretical model is established to analyze the operation of the energy oscillation circuit – (TENG and the inductive circuit) comprehensively. In the model, the TENG is constituted by a series of finite-sized charged planes (FSCP), dielectric materials, and the air-gap. The inductive load is used to promote the oscillation of charge on the TENG. With the newly developed inductive load model, we can observe that, at small load resistance, a boost can be achieved from the voltage on the TENG and the current flowing in the circuit and therefore the energy output observed both from the source (TENG) and on the load (resistor) show increased value. Finally, it is found that for a specific load (resistor) and inductor, the boost performance will reach its peak value for an optimal value of the motion speed for the air-gap between TENG planes (or the variation speed of the mechanic energy). This proposed inductive circuit shows the potential of a standard method for the performance improvement of the energy harvesting scenario using the TENG in particularly for low load impedance.

Error Probability Analysis of NOMA-Based Relay Networks With SWIPT

This letter investigates the error rate performance of relay-assisted non-orthogonal multiple access networks with simultaneous wireless information and power transfer. In particular, we derive a novel closed-form expression for the pairwise error probability (PEP) of all users, which is then used to derive a union bound on the error rate performance. Additionally, we derive an asymptotic closed-form expression of the PEP in the high signal-to-noise ratio regime and demonstrate that the maximum achievable diversity order for the underlying scenario is equal to one. Numerical and simulation results are presented to corroborate the analysis and to investigate the error rate performance of all users under different energy harvesting scenarios.

POMDP-Based Energy Cooperative Transmission Policy for Multiple Access Model Powered by Energy Harvesting

To efficiently use harvested energy, we often consider energy cooperation between transmitter nodes in a multiple access wireless network. However the imperfect observations of current network states will degrade the energy transfer policy. In addition, it is difficult to derive an optimal data transmission policy based on the imperfect observation states. In order to solve these problems, we design a partially observed Markov decision process based energy cooperative transmission policy to maximize long-term system throughput. This policy optimizes the energy transfer and data transmission when we cannot observe energy harvesting states and channel states in a current time interval. We adopt the piecewise linearity of the value function and incremental pruning algorithm to obtain the optimal policy for all states in three energy harvesting scenarios. Simulation results show that the proposed cooperative optimal policy converges fast and produces higher sum throughput compared with other policies. Specifically, this policy could be used in device-to-device communication and vehicular networks.

3D mathematical model of contact-separation and single-electrode mode triboelectric nanogenerators

Based on a set of finite-sized charged planes (FSCP), a simple time-dependent three-dimensional spatial model for the electric potential and electric field in an inhomogeneous medium composed of dielectric materials and metal contacts is proposed and used to assert triboelectric nanogenerator operation. Solving the problem of FSCP makes the three-dimensional spatial model relevant for practical TENG applications and allow for accurate and reliable results. Connecting the metal contacts to an electric resistance, Kirchhoff's law is used to derive a first-order time-dependent differential equation for the mobile charges on the metal contacts and the displacement current. Specially, the displacement current (Maxwell's displacement current) in a TENG equals to the conduction current in the external circuit is obtained. We then consider two important types of triboelectric nanogenerators: the contact-separation (CS) mode and the single-electrode (SEC) mode. A forced movement of the dielectric materials and/or the metal contacts leads to currents flowing in the system and a time-varying electrical potential, and therefore the generation of electrical power. Then, new and more accurate capacitance equations for CS and SEC modes of TENGs are extracted. Several examples of energy harvesting scenarios are finally analyzed.

The Piezoelectric Phenomenon in Energy Harvesting Scenarios: A Theoretical Study of Viable Applications in Unbalanced Rotor Systems

The present paper deals with the promising energy harvesting applications of a composite piezoelectric metal support that is properly designed for the rotor of a mechanical system. The aim is to determine whether the vibrational power coming from the static residual imbalance, which is generally considered to be an undesired and useless side-effect of the rotation, can be converted into electric power and then stored to be used in other applications. The analysis, starting from the Jeffcott rotor model and the piezoelectric constitutive equations, has been carried out by developing an approximated linear model of a piezoelectric support, in order to theoretically evaluate the performance and the feasibility of the proposed system. The accuracy of the exploited analytical model has been validated for both static and dynamic operations by 3D Ansys® Mechanical APDL. Finally, a MatLab®/Simulink® model has been built to simulate the electric behavior of the piezoelectric material, and to estimate the power that it is possible to extract via an alternative/direct current converter (AC/DC converter). The numerical results achieved confirm the effectiveness of the proposed energy-harvesting system.

Energy harvesting two‐way relaying with antenna selection scheme

This study investigates the performance of a bidirectional/two-way relaying scheme with an energy-harvesting relay while amplify-and-forward relaying is performed. With multiple antennas at the relay, the authors propose the use of the max-min antenna selection scheme in the context of an energy harvesting scenario. They show that the proposed scheme attains diversity gain, whereby its end-to-end symbol error probability performance improves with increments in the number of energy harvesting relay antennas. For limited battery capacity at the energy harvesting node, they derive the lower bound of the outage probabilities and observe a good match between the analytical and simulated results. For this scenario, a simple power provisioning technique is proposed to optimise the end nodes' transmission powers. It is observed that the proposed technique saves significantly more transmission energy than the conventional equal power provisioning technique.

NEOFog

Nonvolatile processors have emerged as one of the promising solutions for energy harvesting scenarios, among which Wireless Sensor Networks (WSN) provide some of the most important applications. In a typical distributed sensing system, due to difference in location, energy harvester angles, power sources, etc. different nodes may have different amount of energy ready for use. While prior approaches have examined these challenges, they have not done so in the context of the features offered by nonvolatile computing approaches, which disrupt certain foundational assumptions. We propose a new set of nonvolatility-exploiting optimizations and embody them in the NEOFog system architecture. We discuss shifts in the tradeoffs in data and program distribution for nonvolatile processing-based WSNs, showing how non-volatile processing and non-volatile RF support alter the benefits of computation and communication-centric approaches. We also propose a new algorithm specific to nonvolatile sensing systems for load balancing both computation and communication demands. Collectively, the NV-aware optimizations in NEOFog increase the ability to perform in-fog processing by 4.2X and can increase this to 8X if virtualized nodes are 3X multiplexed.

A Decentralized Optimization Framework for Energy Harvesting Devices

Designing decentralized policies for wireless communication networks is a crucial problem, which has only been partially solved in the literature so far. In this paper, we propose a Decentralized Markov Decision Process (Dec-MDP) framework to analyze a wireless sensor network with multiple users which access a common wireless channel. We consider devices with energy harvesting capabilities, that aim at balancing the energy arrivals with the data departures and with the probability of colliding with other nodes. Over time, an access point triggers a SYNC slot, wherein it recomputes the optimal transmission parameters of the whole network, and distributes this information. Every node receives its own policy, which specifies how it should access the channel in the future, and, thereafter, proceeds in a fully decentralized fashion, with no interactions with other entities in the network. We propose a multi-layer Markov model, where an external MDP manages the jumps between SYNC slots, and an internal Dec-MDP computes the optimal policy in the short term. We numerically show that, because of the harvesting, stationary policies are suboptimal in energy harvesting scenarios, and the optimal trade-off lies between an orthogonal and a random access system.

Optimized Error Probability for Weighted Collaborative Spectrum Sensing in Time- and Energy-Limited Cognitive Radio Networks

In this paper, a collaborative energy-harvesting cognitive radio (CR) network is considered such that the transmitter of the secondary user (SU) is allowed to harvest signal energy of the primary user (PU) when the presence of the PU is detected. The harvested energy is converted to electrical power in order to supply the sensing and transmission energy of SUs. The time frame (time slot) is divided into two phases allocated to sensing (divided into two durations: spectrum sensing and results reporting) and transmission, respectively. The time spanned by the results reporting duration depends on the number of collaborative sensing users, while the time spent on spectrum sensing duration controls the number of sensing samples. A constrained convex optimization problem of the overall probability of error is formulated incorporating constraints on time and energy resources along with PU interference protection presented as a threshold on probability of collision. We use a soft decision rule scheme while considering two energy harvesting scenarios namely, energy surplus and energy deficit. In each scenario, the convexity of the optimization problem is established analytically and the global optimal solution is obtained. Simulation results are provided to demonstrate the impact of the different parameters on the overall system performance as well as to verify the deduced analytical results.

Throughput of an Energy Harvesting Cognitive Radio Network Based on Prediction of Primary User

In this paper, a novel prediction based cooperative spectrum sensing scheme is investigated on the performance of an energy harvesting cognitive radio (CR) network. The spectrum sensing scheme is redesigned to protect the quality of service (QoS) of primary user (PU) and to improve the utilization of spectrum holes. The decision about the PU spectrum status and energy harvesting (RF and non-RF) of a CR node are based on prediction as well as sensing at individual CR level. We consider simultaneous spectrum sensing and energy harvesting scenario through the incorporation of an energy splitting device. A CR harvests from non-RF resources if both the decisions (decision of prediction and decision of spectrum sensing) do not match or if both the decisions match in favor of the absence of PU. On contrary, it harvests from RF resources while both the decisions match in favor of the presence of PU. A CR node transmits only if both decisions indicate the absence of PU. A CR user opportunistically uses the PU spectrum for its transmission purpose under a collision constraint. The collision constraint gives an extra protection to the QoS of PU on rearrival of PU. Novel analytical expressions for detection performance, harvested energy, and network throughput are developed. The impact of prediction and other network parameters such as number of detection frames, number of cooperative CR user, splitting parameter, collision probability on throughput performance is investigated. Improvement in spectrum reuse and energy penalty during harvesting is indicated. Impact of noise power estimation on the sensing performance is also studied.

A Ferroelectric Nonvolatile Processor with 46 $\mu $ s System-Level Wake-up Time and 14 $\mu $ s Sleep Time for Energy Harvesting Applications

Nonvolatile processor (NVP) attracts more and more attentions for its immunity to power loss in energy harvesting scenarios. The overall performance of an NVP is determined by its sleep and wake-up speeds, which refer to how fast the NVP can turn itself off and on when a sudden power failure occurs. To the best of our knowledge, this paper is the first work to improve the system-level sleep/wake-up speed of an energy harvesting NVP. A hybrid CMOS/ferroelectric nonvolatile flipflop (nvFF) and a high-speed voltage detector are designed and integrated in the proposed NVP to jointly minimize its sleep and wake-up time. Measurement results demonstrate 46 μs wake-up time and 14 μs sleep time, which is up to 18 and 24 times speedup over existing works. This approach not only improves the robustness of the NVP to power fluctuations but also brings significant advantages for better utilization of harvested energy.

Cooperative Transmission Scheme of Energy Harvesting Tags

Energy harvesting tags with cooperative communication capabilities are recently emerging as a viable infrastructure for internet of things (IoT) applications. This letter studies the cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of tags to communicate with the reader either directly or by cooperating with neighboring tags. We formulate the problem as a Markov decision process (MDP). The simulation results are provided to show the performance of the cooperative transmission policy under various energy harvesting scenarios.

Cognitive radio network with continuous energy‐harvesting

SummaryIn this paper, the performance of a cooperative cognitive radio (CR) network is investigated under continuous energy harvesting scenario. A CR node harvests energy from both the sources: non‐radio frequency (RF) signal (ambient sources) or from RF signal (primary user signal). It harvests from non‐RF signal during sensing time of its detection cycle, and from both the sources, RF signal and non‐RF signal, during transmission time as per sensing decision. Several novel analytical expressions are developed to indicate the harvested energy, energy reward, energy cost in a detection frame, and throughput. The performance of the CR network is investigated to maximize the throughput considering energy causality constraints and collision constraints. Analytical results are validated through extensive simulation results. Copyright © 2016 John Wiley & Sons, Ltd.

Real-time State Estimation for an Adaptive Vibration Energy Harvesting System

Abstract: Moving horizon estimation (MHE) has proven to be an efficient optimization-based technique to address the problem of joint state and parameter estimation with nonlinearities in system dynamics and constraints. This work aims to propose the application of MHE for a specific nonlinear vibration setup, often used to analyze energy harvesting concepts in the laboratory environment. Using a simulated energy harvesting scenario exhibiting a strongly nonlinear behavior, we focus on the estimation of unmeasured system states and a time-varying structural parameter that can be utilized to maximize the harvested energy, or in structural health monitoring. To exploit the recent algorithmic developments in embedded optimization, we implement the proposed scheme on a low-cost embedded computing platform using automatic code generation. A hardware-in-the-loop setup is used in order to investigate the performance of the real-time MHE scheme, and to quantify the associated computational effort. The results demonstrated in this paper, suggest the real-time feasibility of MHE, and certain practical advantages over a standard Kalman filtering in a vibration energy harvesting system.

Secure 5G Wireless Communications: A Joint Relay Selection and Wireless Power Transfer Approach

In this paper, we investigate the secrecy performance of an energy harvesting relay system, where a legitimate source communicates with a legitimate destination via the assistance of multiple trusted relays. In the considered system, the source and relays deploy the time-switching-based radio frequency energy harvesting technique to harvest energy from a multi-antenna beacon. Different antenna selection and relay selection schemes are applied to enhance the security of the system. Specifically, two relay selection schemes based on the partial and full knowledge of channel state information, i.e., optimal relay selection and partial relay selection, and two antenna selection schemes for harvesting energy at source and relays, i.e., maximizing energy harvesting channel for the source and maximizing energy harvesting channel for the selected relay, are proposed. The exact and asymptotic expressions of secrecy outage probability in these schemes are derived. We demonstrate that applying relay selection approaches in the considered energy harvesting system can enhance the security performance. In particular, optimal relay selection scheme outperforms partial relay selection scheme and achieves full secrecy diversity order, regardless of energy harvesting scenarios.

Clustering Routing Algorithm in Self-energized Wireless Sensor Networks

Aiming at the existing clustering algorithms for self-energized wireless sensor network have neglected the actual environment that different geographic area has acquired different energy harvesting level, which resulting in less cluster heads, large-scale cluster region and network energy-imbalanced in lower energy harvesting areas. In this paper, we propose a novel clustering routing algorithm-CRAS (Clustering Routing Algorithm for Self-energized), which combines with the real energy harvesting scenario to improve the cluster-head election mechanism. Meanwhile, it adopts an adaptive inter-cluster communication mechanism, to sufficiently store and utilize the harvesting energy. Theoretical and simulation results manifest that CRAS algorithm can better keep the default cluster head proportion in the whole network, and it outperforms the two present algorithms in terms of the average residual energy and current available nodes number in the networks.

Deterministic and band-limited stochastic energy harvesting from uniaxial excitation of a multilayer piezoelectric stack

Deterministic and band-limited stochastic energy harvesting scenarios using a multilayer piezoelectric stack configuration are investigated for uniaxial dynamic pressure loading. The motivation for exploring this off-resonant energy harvesting problem derives from typical civil infrastructure systems subjected to dynamic compressive forces in deterministic or stochastic forms due to vehicular or human loads, among other examples of compressive loading. Modeling of vibrational energy harvesters in the existing literature has been mostly focused on deterministic forms of mechanical vibration as in the typical case of harmonic excitation, while the efforts on stochastic energy harvesting have thus far considered second-order systems such as piezoelectric cantilevers. In this paper, we present electromechanical modeling, analytical and numerical solutions, and experimental validations of piezoelectric energy harvesting from harmonic, periodic, and band-limited stochastic excitation of a multilayer piezoelectric stack under axial compressive loading in the off-resonant low-frequency range. The deterministic problem employs the voltage output-to-pressure input frequency response function of the harvester for a given electrical load, which is also extended to periodic excitation. The analytical stochastic electromechanical solution employs the power spectral density of band-limited stochastic excitation to predict the expected value of the power output. The first one of the two numerical solution methods uses the Fourier series representation of the excitation history to solve the resulting ordinary differential equation, while the second method employs an Euler–Maruyama scheme to directly solve the governing electromechanical stochastic differential equation. The electromechanical models are validated through several experiments for a multilayer PZT-5H stack under harmonic and band-limited stochastic excitations at different pressure levels. The figure of merit is also extracted for this particular energy harvesting problem to choose the optimal material. Soft piezoelectric ceramics (e.g. PZT-5H and PZT-5A) offer larger power output as compared to hard ceramics (e.g. PZT-8), and likewise, soft single crystals (e.g. PMN-PT and PMN-PZT) produce larger power as compared to their hard counterparts (e.g. PMN-PZT-Mn); and furthermore, single crystals (e.g. PMN-PT and PMN-PZT) generate more power than standard ceramics (e.g. PZT-5H and PZT-5A) for low-frequency, off-resonant excitation of piezoelectric stacks.

Thermoelectric energy harvesting system for demonstrating autonomous operation of a wireless sensor node enabled by a multipurpose interface

This paper demonstrates the autonomous operation of a wireless sensor node exclusively powered by thermoelectric energy harvesting. Active operation of a wireless sensor system is demonstrated successfully by means of an on-line programmable emulation kit that enables various thermoelectric energy harvesting scenarios. Moreover, this emulation kit accomplishes autonomous wireless sensor node operation by interfacing a small-scaled thermogenerator via a CMOS integrated autonomous multipurpose energy harvesting interface circuit performing maximum power point tracking.

Energy harvesting from human motion: an evaluation of current nonlinear energy harvesting solutions

The concept of harvesting electrical energy from ambient vibration sources has been a popular topic of research in recent years. Recently, the realisation that the majority of ambient vibration sources are often stochastic in nature has led to a large body of work which has focused on the response of energy harvesters to random excitations – most of which approximate environmental excitations as being Gaussian white noise. Of particular interest here are recent findings which demonstrate the advantages that Duffing-type nonlinearities can introduce into energy harvesters. The aim of this paper is to identify how well these results can be applied to that of a real energy harvesting scenario. More specifically, the response of an energy harvester to excitation via human motion is studied using digital simulations in conjunction with acceleration data obtained from a human participant. As well as assessing whether Duffing-type nonlinearities can have a beneficial impact on device performance this paper aims to investigate whether Gaussian white noise can indeed be used as a good approximation for this particular ambient vibration source.

Design Considerations for Ultra-Low Energy Wireless Micro Sensor Nodes

This tutorial paper examines architectural and circuit design techniques for a micro sensor node operating at power levels low enough to enable the use of an energy harvesting source. These requirements place demands on all levels of the design. We propose architecture for achieving the required ultra-low energy operation and discuss the circuit techniques necessary to implement the system. Dedicated hardware implementations improve the efficiency for specific functionality, and modular partitioning permits fine-grained optimization and power-gating. We describe modeling and operating at the minimum energy point in the transmitter and the ADC. A micro sensor node using the techniques we describe can function in an energy-harvesting scenario