Random Energy Research Articles

Energy Harvesting Wireless Sensor Networks With Channel Estimation: Delay and Packet Loss Performance Analysis

This paper considers a single-source status monitoring system with energy harvesting in the context of applications where keeping information up-to-date is of primary interest. Specifically, a sensor node, relying on harvested energy and operating according to a harvest-then-use protocol, estimates the channel state to decide whether to perform or defer data delivery to a sink. The sink keeps track of the system status through the successfully delivered updates. To comprehensively evaluate the performance of the proposed scheme, we analytically derive the exact-closed form expressions of the packet loss probability, the age of information and the update interval metric statistics considering both constant-rate and random energy arrival processes and taking into account both the time and energy costs of sensing, transmitting and estimating the channel state. We asymptotically obtain the necessary conditions under which estimating the channel state before transmitting, despite the associated time and energy costs, allow to efficiently manage the harvested energy by avoiding erroneous transmissions and performs strictly better than transmitting without estimating the channel state. Numerical results demonstrate that in most cases, estimating the channel state before transmitting significantly reduces the packet loss probability, the age of information and the update interval of node-sink transmission.

Study of Energy Harvesting from Low-Frequency Vibration with Ferromagnetic Powder and Non-magnetic Fluid

The movement of the creature and the almost wave in the ocean is a low vibration of random energy with a frequency range of 0.1–10 Hz. Because of its low frequency, the opinion has been that electrical energy generation from this low-frequency wave motion through the electromagnetic induction method is difficult. In this study, an electrical generator was created by the electromagnetic induction method by putting a small mass of ferromagnetic powder in nonmagnetic fluid. A broadband vibration energy harvesting model was created in which vibrations are broadened through a multi-degree of freedom oscillation system using ferromagnetic powder. To generate electricity from low-frequency vibrations (1 Hz or less), a non-resonant type model was created by adding fluid to the ferromagnetic powder model and the simulation results confirmed using computational fluid dynamics by creating a working energy harvesting device.

Storage or No Storage: Duopoly Competition Between Renewable Energy Suppliers in a Local Energy Market

This paper studies the duopoly competition between renewable energy suppliers with or without energy storage in a local energy market. The storage investment brings the benefits of stabilizing renewable energy suppliers' outputs, but it also leads to substantial investment costs as well as some surprising changes in the market outcome. To study the equilibrium decisions of storage investment in the renewable energy suppliers' competition, we model the interactions between suppliers and consumers using a three-stage game-theoretic model. In Stage I, at the beginning of the investment horizon, suppliers decide whether to invest in storage. Once such decisions have been made, in the day-ahead market of each day, suppliers decide on their bidding prices and quantities in Stage II, based on which consumers decide the electricity quantity purchased from each supplier in Stage III. In the real-time market, a supplier is penalized if his actual generation falls short of his commitment. We characterize a price-quantity competition equilibrium of Stage II, and we further characterize a storage-investment equilibrium in Stage I incorporating electricity-selling revenue and storage cost. Counter-intuitively, we show that the uncertainty of renewable energy without storage investment can lead to higher supplier profits compared with the stable generations with storage investment due to the reduced market competition under random energy generation. Simulations further illustrate results due to the market competition. For example, a higher penalty for not meeting the commitment, a higher storage cost, or a lower consumer demand can sometimes increase a supplier's profit. We also show that although storage investment can increase a supplier 's profit, the first-mover supplier who invests in storage may benefit less than the free-rider competitor who chooses not to invest.

On the efficacy of charging a battery using a chaotic energy harvester

Introduction of stiffness nonlinearities to broaden the frequency bandwidth of vibratory energy harvesters has the adverse influence of complicating the response behavior of the harvester. As such, unlike linear energy harvesters, for which direct performance metrics can be easily developed, it is not always easy to develop metrics to assess the performance of nonlinear energy harvesters. One particular issue arises when the harvester operates in its chaotic regime resulting in an unpredictable response, under which the harvester’s performance is hard to assess. In this paper, we present a statistical technique to estimate the charging time of a battery being charged by a chaotic vibratory input. The proposed approach, which accounts for the presence of a rectifier circuit, a buck converter, and the dependence of the battery voltage on the state of charge, only requires the knowledge of the probability density function of the open-circuit voltage of the harvester. Using the proposed technique, it is also possible to obtain the optimal duty cycle of the buck converter. Results of the proposed methodology were compared to numerical data generated using MATLAB’s Simscape toolbox demonstrating excellent agreement. Not only does the proposed technique provide a valuable tool to assess performance of a chaotic energy harvester, but it can also be easily applied to other chaotic and random energy sources.

Convergence Time to Equilibrium of the Metropolis Dynamics for the GREM

We study the convergence time to equilibrium of the Metropolis dynamics for the Generalized Random Energy Model with an arbitrary number of hierarchical levels, a finite and reversible continuous-time Markov process, in terms of the spectral gap of its transition probability matrix. This is done by deducing bounds to the inverse of the gap using a Poincar\'e inequality and a path technique. We also apply convex analysis tools to give the bounds in the most general case of the model.

Control of superconducting magnetic energy storage systems in grid‐connected microgrids via memetic salp swarm algorithm: An optimal passive fractional‐order PID approach

This study proposes an optimal passive fractional-order proportional-integral derivative (PFOPID) control for a superconducting magnetic energy storage (SMES) system. First, a storage function is constructed for the SMES system. Moreover, it has carefully reserved favourable terms for purpose of making full use of the physical properties of the SMES systems, while a fractional-order PID (FOPID) structure is adopted as the attached input for purpose of further improving its dynamical responses. In addition, a memetic salp swarm algorithm is adopted to optimise and tune the control gains of the proposed method, which can achieve a suitable trade-off between global exploration and local exploitation, so as to realise the optimal control performance. Case studies, e.g. (i) active and reactive power supply, (ii) system recovery capability under power grid fault, (iii) power support under the infiltration of random renewable energy and (iv) robustness of system parameter uncertainty is studied, and the availabilities and benefits of POFPID control over PID control, FOPID control and passive control based on interconnection and damping assignment passivity-based control are comprehensively investigated. Lastly, the feasibility of PFOPID control is checked by hardware-in-the-loop experiment based on a dSpace.

Decentralized Random Energy Allocation for Massive Non-Orthogonal Code-Division Multiple Access

This work studies the spectral efficiency achievable when a very large number of terminals are connected simultaneously to a central node (uplink) through independent and identically-distributed flat-fading channels. Assuming that terminals only have statistical channel state information (CSI), the optimum random transmitted-energy allocation is formulated considering a non-orthogonal direct-sequence code-division multiple access (DS-CDMA) where all users transmit using the same modulation and error correcting code and the receiver implements successive interference cancellation (SIC). Focusing on low-power terminals, optimization is carried out by imposing constraints on both the average and peak per-user transmitted energy. Simulations have revealed that a limited number of random energy levels, whose number is determined by the channel power gain variance, is sufficient to achieve approximately the maximum spectral efficiency that would be obtained under direct optimization of the received energy profile.

Influence of restricted operating space on the performance of random vibration energy harvesting

The ambition to create self-powered microscale electrical devices motivates scientific and industrial communities to investigate the energy harvesting technique, especially working in random vibration circumstances. The mechanical response of the random vibration system may approach infinity with small probability, and then the restricted operating space of the energy harvesting system will unavoidably induce the occurrence of collision interaction. Here, the random mechanical vibration and electrical output of the vibration energy harvesting system including inelastic collision are investigated, in which the random excitation is described by Gaussian white noise, while the collision interactions are described by the transient impact model and inelastic contact model, respectively. Introducing the generalized harmonic transformation of mechanical states and adopting a slow-varying process assumption of amplitude and averaged frequency, the output voltage can be explicitly expressed as the function of displacement, velocity, and system total energy by directly integrating the linear electrical equation. The transient impact interaction is equivalent to an effective damping with energy-dependent damping coefficient, while the inelastic contact interaction is equivalent to an effective damping and an affiliated potential energy. The averaged equations with respect to mechanical energy are then derived through the stochastic averaging technique. The stationary probabilistic density function of mechanical states is established by solving the reduced Fokker–Plank–Kolmogorov equation, and then the statistical quantities of electrical voltage are obtained by the relation between voltage and mechanical states. The effectiveness and precision of the analytical procedure are validated through the results from Monte Carlo simulations, and the influence of collision interaction on the performance of energy harvesting is discussed in detail. Also, for the energy harvesting system excited by colored noise, the influence of collision interaction on the performance is evaluated through Monte Carlo simulations.

The parabolic Anderson model on the hypercube

We consider the parabolic Anderson model ∂∂tvn=κΔnvn+ξnvn on the n-dimensional hypercube {−1,+1}n with random i.i.d. potential ξn. We study vn at the location of the kth largest potential, xk,2n. Our main result is that, for a certain class of potential distributions, the solution exhibits a phase transition: for short time scales vn(tn,xk,2n) behaves like a system without diffusion and grows as exp{(ξn(xk,2n)−κ)tn}, whereas, for long time scales the growth is dictated by the principal eigenvalue and the corresponding eigenfunction of the operator κΔn+ξn, for which we give precise asymptotics. Moreover, the transition time depends only on the difference ξn(x1,2n)−ξn(xk,2n). One of our main motivations is to investigate the mutation–selection model of population genetics on a random fitness landscape, which is given by the ratio of vn to its total mass, with ξn corresponding to the fitness landscape. We show that the above mentioned phase transition translates to the mutation–selection model as follows: a population initially concentrated at xk,2n moves completely to x1,2n on time scales where the transition of growth rates occurs. The class of potentials we consider includes the Random Energy Model (REM) which is studied in the statistical physics literature as one of the main examples of a random fitness landscape.

High-speed vehicle–slab track coupled vibration analysis of the viscoelastic-plastic dynamic properties of rail pads under different preloads and temperatures

The viscoelastic-plastic dynamic properties of rail pads were are not adequately accounted for in the traditional vehicle–track coupled dynamic model. To investigate the influence of the viscoelastic-plastic dynamic properties of rail pads on the high-speed vehicle–track coupled vibrations, we obtained the viscoelastic-plastic dynamic properties of rail pads first by a series of laboratory tests, after which we described these properties theoretically by a modified Fractional Derivative Zener (FDZ) model and a traditional Berg friction model. A modified vertical vehicle–slab track coupled dynamic model was established by introduction of the modified FDZ and traditional Berg models for rail pads to investigate the influence of the viscoelastic-plastic dynamic properties of the rail pads on the high-speed vehicle–slab track coupled vibration responses under various preloads and temperatures. The FDZ and Berg models for rail pads improved the calculation accuracy of the high-speed vehicle–slab track coupled vibration responses, compared with the traditional KV model for rail pads, especially in the dominant high frequency range. The dynamic plastic properties of the rail pads effectively suppressed the high-frequency wheel-rail forces and yet increased the high-frequency vibration responses of the track substructures under the rail. Low temperatures and increased preloads on rail pads had a similar effect on the vehicle–track coupled vibrations. Increasing the preload on rail pads or decreasing the temperature increased the wheel-rail random excitation energy and its dominant frequencies, increased the vibration responses of the wheel-set and the track substructure under the rail, and decreased the vibrations of the rail at nearly all frequencies. Highlights The dynamic viscoelasticity and plasticity of rail pad under preloads and temperatures were tested. A modified FDZ model for the dynamic viscoelastic properties of rail pads was proposed. The dynamic plastic properties of rail pads can decrease the high-frequency wheel-rail forces. The dynamic plastic properties of rail pads can increase the high-frequency vibration under the rail. Low temperatures and increased preloads on rail pads had a similar effect on vehicle/track vibration.

Effective one-particle energies from generalized Kohn-Sham random phase approximation: A direct approach for computing and analyzing core ionization energies.

Generalized-Kohn-Sham (GKS) orbital energies obtained self-consistently from the random phase approximation energy functional with a semicanonical projection (spRPA) were recently shown to rival the accuracy of GW quasiparticle energies for valence ionization potentials. Here, we extend the scope of GKS-spRPA correlated one-particle energies from frontier-orbital ionization to core orbital ionization energies, which are notoriously difficult for GW and other response methods due to strong orbital relaxation effects. For a benchmark consisting of 23 1s core electron binding energies (CEBEs) of second-row elements, chemical shifts estimated from GKS-spRPA one-particle energies yield mean absolute deviations from experiment of 0.2 eV, which are significantly more accurate than the standard GW and comparable to Δ self-consistent field theory without semiempirical adjustment of the energy functional. For small ammonia clusters and cytosine tautomers, GKS-spRPA based chemical shifts capture subtle variations in covalent and noncovalent bonding environments; GKS-spRPA 1s CEBEs for these systems agree with equation-of-motion coupled cluster singles and doubles and ADC(4) results within 0.2-0.3 eV. Two perturbative approximations to GKS-spRPA orbital energies, which reduce the scaling from O(N6) to O(N5) and O(N4), are introduced and tested. We illustrate the application of GKS-spRPA orbital energies to larger systems by using oxygen 1s CEBEs to probe solvation and packing effects in condensed phases of water. GKS-spRPA predicts a lowering of the oxygen 1s CEBE of approximately 1.6-1.7 eV in solid and liquid phases, consistent with liquid-jet X-ray photoelectron spectroscopy and gas phase cluster experiments. The results are rationalized by partitioning GKS-spRPA electron binding energies into static, relaxation, and correlation parts.

Regenesis and quantum traversable wormholes

Recent gravity discussions of a traversable wormhole indicate that in holographic systems signals generated by a source could reappear long after they have dissipated, with the need of only performing some simple operations. In this paper we argue the phenomenon, to which we refer as “regenesis”, is universal in general quantum chaotic many-body systems, and elucidate its underlying physics. The essential elements behind the phenomenon are: (i) scrambling which in a chaotic system makes out-of-time-ordered correlation functions (OTOCs) vanish at large times; (ii) the entanglement structure of the state of the system. The latter aspect also implies that the regenesis phenomenon requires fine tuning of the initial state. Compared to other manifestations of quantum chaos such as the initial growth of OTOCs which deals with early times, and a random matrix-type energy spectrum which reflects very large time behavior, regenesis concerns with intermediate times, of order the scrambling time of a system. We also study the phenomenon in detail in general two-dimensional conformal field theories in the large central charge limit, and highlight some interesting features including a resonant enhancement of regenesis signals near the scrambling time and their oscillations in coupling. Finally, we discuss gravity implications of the phenomenon for systems with a gravity dual, arguing that there exist regimes for which traversability of a wormhole is quantum in nature, i.e. cannot be associated with a semi-classical spacetime causal structure.

Energy-economic resilience with multi-region input–output linear programming models

In this work we propose an input–output linear programming model to study the energy resilience of a multi-region economy that accounts for the inter-sectoral and inter-regional dependencies in the economic structure. The model computes the impacts of random energy production disruptions on the entire multi-region input–output system in the form of final demand deficits. We then propose a formulation to evaluate the energy resilience of the system based on computing the largest set of disruptions, or what is termed as resilience guarantee levels, that can be sustained by the system within given demand deficit budgets. A computational study is then performed using a 3-region-42-sector model based on China's 2012 multi-regional input–output table. The results show that regional trade barriers, coal-to-gas switch policies and technological efficiency of selected energy-intensive industries can influence China's energy resilience significantly. This can provide the policy-makers important guidance on improving energy resilience in a systematic manner.

A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes

A mobile Wireless Sensor Network (mWSN) is composed of a large number of tiny, inexpensive resource-constrained sensors scattered in the field of interest, with the sink node or the data collector moving around the field. One fundamental concern of an mWSN is to provide application-specific coverage of the area under surveillance. The reliability of an mWSN depends on sensing area coverage, network connectivity, and data handling capacity of the mWSN in the presence of multi-state sensors. To mention here, each sensor node during its life cycle may exist in ACTIVE, SLEEP, RELAY, IDLE or FAIL states due to hardware failure, random duty cycle and/or energy limitations. Under such constraints, to quantify application-specific coverage oriented reliability, a new coverage-reliability index, CORE, is introduced. CORE gives a measure of the ability of a sensor network with multi-state nodes to satisfy the application-specific coverage area requirement with reliable data delivery to the mobile sink. A Monte-Carlo Markov Chain simulation approach is proposed for evaluating CORE. The conducted computational experiments are carried on mWSNs of various sizes to demonstrate the versatility of the proposed approach.

Robust distributed optimization for energy dispatch of multi-stakeholder multiple microgrids under uncertainty

This paper addresses the energy dispatch problem for multi-stakeholder multiple microgrids (MMGs) under uncertainty while considering independent market operators (IMOs) based energy trading forms. Firstly, a collaborative hierarchical dispatch framework is proposed to adapt to decentralized multiple stakeholders and coordinate energy trading between IMOs and microgrids (MGs). And then this framework is further decomposed into different independent optimization problems for stakeholders based on an analytical target cascading (ATC) algorithm, in which Lagrangian penalty terms are introduced to ensure consistency in energy trading. In these optimization problems, energy trading and production of an individual MG is formulated as a two-stage adaptive robust optimization model to hedge against uncertainties from random renewable energy sources and loads. Moreover, in order to realize parallel computing for all independent optimization problems, a diagonal quadratic approximation method is applied to linearize quadratic terms. We integrate the ATC algorithm with a column-and-constraint generation algorithm to derive robust energy dispatch schemes in parallel. Finally, simulations on different cases are conducted to testify the rationality and validity of the proposed robust distributed energy dispatch approach. The results show that the hierarchical energy dispatch framework with IMOs has advantages over that without IMOs. Moreover, the proposed approach can reduce the impacts of uncertainties on distributed decision making of multiple stakeholder and enhance the computational efficiency.

A High-Voltage Energy-Harvesting Interface for Irregular Kinetic Energy Harvesting in IoT Systems with 1365% Improvement Using All-NMOS Power Switches and Ultra-low Quiescent Current Controller.

An energy-harvesting interface for kinetic energy harvesting from high-voltage piezoelectric and triboelectric generators is proposed in this paper. Unlike the conventional kinetic energy-harvesting interfaces optimized for continuous sinusoidal input, the proposed harvesting interface can efficiently handle irregular and random high voltage energy inputs. An N-type mosfet (NMOS)-only power stage design is introduced to simplify power switch drivers and minimize conduction loss. Controller active mode power is also reduced by introducing a new voltage peak detector. For efficient operation with potentially long intervals between random kinetic energy inputs, standby power consumption is minimized by monitoring the input with a 43 pW wake-up controller and power-gating all other circuits during the standby intervals. The proposed harvesting interface can harvest energy from a wide range of energy inputs, 10 s of nJ to 10 s of µJ energy/pulse, with an input voltage range of 5–200 V and an output range of 2.4–4 V under discontinuous as well as continuous excitation. The proposed interface is examined in two scenarios, with integrated power stage devices (maximum input 45 V) and with discrete power stage devices (maximum input 200 V), and the harvesting efficiency is improved by up to 600% and 1350%, respectively, compared to the case when harvesting is performed with a full bridge rectifier.

Reliability Evaluation and Reliability-Based Optimal Design for Wireless Sensor Networks

Wireless sensor networks (WSNs) are widely applied in many fields. It is of concern to evaluate and improve the reliability of a WSN to ensure a highly reliable operation in practice. In this paper, the reliability of WSNs is analyzed by considering random failures, energy consumption, environmental randomness, and interference, due to their nonnegligible effects. For a typical WSN consisting of multiple sensor nodes and a sink node, we suppose that the WSN is functional if the number of the sensor nodes that are interconnected and connected to the sink node is no less than a minimum required number. Two novel reliability indices, the generalized terminal reliability, and the average generalized terminal reliability, are proposed to assess the reliability of WSNs, and their calculation methods are provided based on the algebraic graph theory and Monte Carlo simulations. Moreover, an optimization method with three stages is presented to comprehensively optimize the design of a WSN from the view point of reliability. Finally, a numerical example is given to illustrate the effectiveness of the proposed methods.

Non-ergodic extended phase of the Quantum Random Energy model

The concept of non-ergodicity in quantum many body systems can be discussed in the context of the wave functions of the many body system or as a property of the dynamical observables, such as time-dependent spin correlators. In the former approach the non-ergodic delocalized state is defined as the one in which the wave functions occupy a volume that scales as a non-trivial power of the full phase space. In this work we study the simplest spin glass model and find that in the delocalized non-ergodic regime the spin–spin correlators decay with the characteristic time that scales as non-trivial power of the full Hilbert space volume. The long time limit of this correlator also scales as a power of the full Hilbert space volume. We identify this phase with the glass phase whilst the many body localized phase corresponds to a ’hyperglass’ in which dynamics is practically absent. We discuss the implications of these findings to quantum information problems.

Type synthesis of parallel mechanisms capturing wave energy

Wave energy is clean, renewable, and abundant, awaiting exploitation. A wide range of wave energy converters have been proposed so far. Oscillating body systems are an important class of wave energy converters. Many mechanisms have been invented to absorb the random wave energy. Nowadays, there is a lack of method to design the mechanism for oscillating body systems to extract the wave energy. Parallel mechanism has the advantages of high stiffness and high load, which are suitable for design of the mechanism for wave energy converters. In this paper, a procedural method based on the generalized function ( G F) sets theory is proposed to design parallel mechanisms to capture wave energy. Using this method, numerous parallel mechanisms have been obtained, which provides the foundation of the development of wave energy converters.

Towards crack paths simulations in media with a random fracture energy

Simple probabilistic models of fracture of 3D polycrystals involving transgranular and intergranular cracks are proposed, based on undamaged paths and appropriate percolation thresholds. In a second part, we propose theoretical extensions of phase field models for crack initiation and propagation to the case of locally heterogeneous and anisotropic fracture energy, and their implementation to get full field solutions by means of iterations of Fourier transforms to replace the standard finite element approach.