Nonlinear Power Research Articles

Risk-based preventive energy management for resilient microgrids

A microgrid's energy management system (EMS) is typically formulated as a deterministic optimization problem. However, more risks and uncertainties are emerging due to the increasing complexity of the power system structure with intelligent distributed energy integration. As a result, different types of risks must be considered while implementing the EMS to improve system resiliency. In this paper, a risk-based EMS is introduced for islanded microgrids. A scenario-based optimization method is formulated for the EMS, where each system component's probability of failure (PoF) is considered in each scenario. In addition, the loads are classified into critical, semi-critical, and non-critical loads to prioritize serving the essential loads during a shortage of generation resources in microgrids. The nonlinear power flow equation of the new problem formulation is relaxed into a convex form to reduce the computational burden. In detail, the system's resiliency is improved by employing three functionalities in the EMS as a preventive measure: a) prioritizing to serve the critical loads, b) lowering the total amount of load served to mitigate the impact of the failure of any system component, and c) reducing the dependency on the generation resources with high PoF. The proposed preventive and risk-based EMS is validated against IEEE-14, 30, and 118 bus systems. The results demonstrate that the proposed EMS sheds more loads than the base EMS, based on the PoF of each system component, due to the knowledge that risks of failure of any component may induce a cascading failure and even blackout if only base EMS is provided. Moreover, the proposed EMS precisely considers the criticality of loads for curtailment to match the available system resources. The curtailment indirectly improves the system's resiliency by increasing the chance of survivability in the islanded mode with the probability of future component failure.

Effect of asymmetric proof mass and size-dependency in flexoelectric nanoharvester subjected to base and restraint forces

The piezoelectric and flexoelectric techniques are of great interest among the scientific fraternity, especially for the design of vibration-based micro/nano energy harvesters. The development of such energy harvesters in the micro/nanoscale has a huge potential, mostly in wireless networks and IoT-based applications. The present work thus formulates novel nanostructure-based analytical models of energy harvesters with asymmetric proof mass considering nonlocal flexoelectricity, geometrical nonlinearity, mid-plane stretching, harmonic base, and axially restraint forces. Using non-classical Euler-Bernoulli nanobeam and Hamilton’s principle, governing differential equation of motion has been derived. Analytical solutions have been obtained to compute the eigenfrequencies and subsequent modes of vibration concerning various systems’ physical and geometric variables. Nonlinear steady-state voltage and power characteristics thereafter have been investigated and studied their local stability and bifurcation for primary and sub-harmonic resonant conditions. The influences of performance factors associated with asymmetrically proof mass, nonlocal elasticity, and time-dependent base and restraint forces on the nonlinear voltage and power output using frequency characteristics criterion. These results have been validated with the findings using COMSOL-2D, and interestingly, mean voltage and power responses from linear models are found to be highly consistent with findings in COMSOL 2D. The present outcome shows how the asymmetric proof mass and nanoscale effect create disparities in harvesting energy performance and, simultaneously, how important their role is to avoid any undesirable structural instability. The present studies together can strengthen the significance of size-dependency and asymmetric proof mass while designing a nanoscale generator in the presence of harmonic excitation.

Second harmonic generation and two photon absorption assisted power limiting mechanism of l-Phenylalanine (LPA) - poly-ethylene-oxide (PEO) electrospun nanofibers

Nanofibers consisting of organic nonlinear optical l-Phenylalanine (LPA) nanocrystals embedded in poly-ethylene-oxide (PEO) polymer were synthesized by the electrospinning technique. The preferred crystallographic orientation of the organic molecules that crystallized inside the nanofibers was demonstrated through X-ray diffraction and calculations show that the average crystallite size is around 28 nm. SEM images clearly show the formation of smooth fibers with average diameter of 246 nm. The emission of green light from the nanofiber powder sample approved the second harmonic generation (SHG) under the excitation of Nd: YAG laser (1064 nm). Further the generation of second harmonic from the fibers was confirmed by nonlinear microscope imaging and power dependent SHG studies, performed using femtosecond fiber laser (1040 nm). The nonlinear absorption and its power limiting characteristics of LPA-PEO electro-spun nanofibers were studied utilizing the Z-scan method employing Q switched Nd: YAG laser as an excitation source (532 nm, 5 ns, 10 Hz). Open aperture Z-scan measurement (with intensity 1.23 × 1012 W/m2 and 2.4623 × 1012 W/m2) revealed the reverse saturable absorption property of LPA-PEO nanofibers. The existence of a sequential two-photon absorption process involving real resonant intermediate states has been demonstrated by the intensity dependent two-photon absorption coefficient. The usefulness of LPA optical fibers as power limiters is ensured by their lower optical limiting threshold than other optical limiting materials.

Fuzzy adaptive distributed synchronization control of uncertain multi-agents systems with unknown input power and sector nonlinearities

This article studies the synchronization problem of a class of nonlinear leader-following systems with multiple constraints, where each follower not only has un-modeled dynamics but also is subject to unknown higher input power and sector nonlinearity. Utilizing the unknown function approximation capability of fuzzy logic systems, a novel fuzzy adaptive distributed control strategy is proposed. Comparing with the existing results, multiple constraints are also considered simultaneously in the strategy. Furthermore, some shortcomings in the related literatures of MASs have been overcome. In addition, the assumption about system uncertainties have been relaxed or removed. Based on Lyapunov stability theory and graph theory, it is proven that each follower can asymptotically synchronize to the leader and the synchronization errors converge the origin’s neighborhood. Finally, to verify the effectiveness of the developed control strategy, simulation results of an example are given.

Asymptotic stability manifolds for solitons in the generalized Good Boussinesq equation

We consider the generalized Good-Boussinesq model in one dimension, with power nonlinearity and data in the energy space H1×L2. This model has solitary waves with speeds −1<c<1. When |c| approaches 1, Bona and Sachs showed orbital stability of such waves. It is well-known from a work of Liu that for small speeds solitary waves are unstable. In this paper we consider in more detail the long time behavior of zero speed solitary waves, or standing waves. By using virial identities, in the spirit of Kowalczyk, Martel and Muñoz, we construct and characterize a manifold of even-odd initial data around the standing wave for which there is asymptotic stability in the energy space.

A Lyapunov-based nonlinear direct power control for grid-side converters interfacing renewable energy in weak grids

A Lyapunov-based nonlinear direct power control for grid-side converters interfacing renewable energy in weak grids

Maximum power point tracking for grid-connected photovoltaic system using Adaptive Fuzzy Logic Controller

Photovoltaic (PV)-based energy solutions are utilized around the world as the demand for energy from renewable energy sources continues to increase. The advantages of a renewable energy source (RES)-based PV system are that it is environmentally friendly and needs less maintenance. The provision of consistent voltage is necessary for PV systems that are connected to the grid. The sun's irradiation varies often during the day. The availability of grid-connected PV systems can be increased by implementing an Adaptive Fuzzy Logic Controller (AFLC) with nonlinear reactive power and a DC-Link voltage controller. To solve the issue of resilience against uncertainties and outside disruptions, a state-variable control strategy is adopted. The controller uses maximum power point tracking (MPPT) to ensure that the utility system receives the most electricity possible in situations with fluctuating solar radiation. Results from the proportional-integral (PI) and Fuzzy Logic Controllers are compared to the collected results (FLC).

SWIPT Enabled Cooperative Cognitive Radio Sensor Network With Non-Linear Power Amplifier

In this work, performance of a simultaneous wireless information and power transfer (SWIPT) enabled cooperative cognitive radio sensor network (CRSN) is explored over generalized Nakagami-m faded channels. A time switching (TS) protocol for SWIPT is used and the impact of TS factor on energy harvesting and information transmission phases, and information processing and broadcasting phases are considered. The cooperative CRSN consists of a pair of primary nodes (PNs) and sensor nodes (SNs), where one of the SWIPT enabled SN provides cooperative relaying for PNs communication by utilizing amplify-and-forward protocol. The overlay spectrum sharing protocol is used at the SN, which supports PNs communication along with its own transmission and resolves the spectrum scarcity issue. The impact of a non-linear power amplifier (NLPA) is also considered on the network performance. The analytical expressions of outage probability (OP), asymptotic OP, system throughput, and energy efficiency are obtained over Nakagami-m faded channels for arbitrary m. Further, the analytical expressions of ergodic capacity (EC) and asymptotic EC are obtained. The impact of NLPA and other system parameters on the performance of the considered network are highlighted. Finally, the obtained analytical expressions are validated through Monte-Carlo simulations.

A 2D-LUT Scheme Design for Complex-Valued Spline Adaptive Filter

This brief presents a two dimensional Look-Up-Table (2D-LUT) scheme for complex-valued (CV) spline adaptive filter. The key idea of this structure is to model a complex-valued nonlinear static function by implementing the Carstesian product of two univariate cubic uniform B-spline curves. Therefore, the real and imaginary components of the system complex-valued output can be readily achieved hinging on two different sets of spline control point respectively, each of which is stored in a 2D-LUT separately. In addition, as an extension of the real-valued (RV) sign spline adaptive algorithm, the CV counterpart is also derived to update both the weight coefficients of the linear subsystem and spline control points associated with 2D-LUTs. Simulations on the identification of RF nonlinear power amplifier (PA) show that the proposed scheme outperforms the existing methods in terms of estimation accuracy against impulsive noises, as well as lower computational complexity.

A CONSTRUCTIVE INVESTIGATION BY THE METHODS OF TWO-SIDED APPROXIMATIONS OF BOUNDARY PROBLEMS FOR SECOND-ORDER SEMILINEAR ELLIPTIC EQUATIONS

The paper considers the first boundary value problem for a second-order semilinear elliptic equation. Problems of this class often arise in the modeling of processes occurring in chemistry, physics, biology, etc. A special place among the methods of analysis of the problems under consideration is occupied by the so-called constructive research methods, which allow not only to prove the existence of a problem solution, but also offer an algorithm for finding it with a given accuracy. For a constructive study of a nonlinear boundary value problem, it is proposed to use two versions of the method of two-sided approximations. Both methods are based on the transition from a differential problem to an equivalent nonlinear integral equation (using the Green’s function or using the Green-Rvachev’s quasi-function), which is analyzed by methods of the theory of nonlinear operators in semi-ordered Banach spaces. Conclusions about the existence of positive solutions of the constructed integral equations and the two-sided convergence of successive approximations to these solutions are made on the basis of the results of V.I. Opojcev on the solvability of nonlinear equations with a heterotone operator. The practical implementation of the method of two-sided approximations based on the use of the Green's function has certain limitations associated with the need to have an explicit expression for this function, which narrows the range of areas in which the method can actually be applied. The method of two-sided approximations, based on the use of the Green-Rvachev’s quasi-function, which can be constructed using the apparatus of the R-functions theory for regions of sufficiently arbitrary geometry, is free from this shortcoming. The proposed methods are illustrated by computational experiments for elliptic equations with Laplace and Helmholtz operators and heterotone power nonlinearity in a number of two- and three-dimensional domains. The results of both methods of two-sided approximations were compared with each other.

On the Role of Axial Neutron Flux Mode Excitation in BWR Stability and Nonlinear Oscillations

Neutron flux modal decomposition is a key tool for analytical and reduced order modeling of boiling water reactor (BWR) stability and oscillations. As a minimum, the fundamental flux mode is used for representing global oscillations while the addition of at least one azimuthal harmonic is needed for simulating the regional out-of-phase mode. Unlike the fundamental and first azimuthal modes, the excitation of an axial flux mode alters the axial power shape but not the total power in the channel and therefore cannot be self-sustained when coupled to density wave–generated reactivity, presumably explaining why it has not been explicitly included in previously published models. Although not self-sustained, the axial mode excitation driven by density wave propagation and interactions with other spatial modes play important roles in interpreting observed BWR stability and oscillations particularly in the nonlinear regime when the oscillation magnitude is large. In this paper, the characteristics of the steady-state axial modes are presented, and their impact on oscillation dynamics for small and large amplitudes of both the global and the regional oscillations is studied using reduced order analytical tools. Aside from the oscillating component, our research results identify an average nonzero axial mode component to develop during limit cycle oscillations that causes the average axial power profile to shift toward the bottom of the core and thus contributes a negative reactivity component. The emergence of this nonzero average axial mode component and the associated negative reactivity were found to diminish the power increase due to global mode power oscillations and contribute to nonlinear stabilization of regional oscillations. The physical interpretation of nonlinear power oscillations with the inclusion of the axial mode component resolves previously unexplained results obtained from high-fidelity numerical models.

Enhanced Distributed Non-Linear Voltage Regulation and Power Apportion Technique for an Islanded DC Microgrid

There is a growing focus on exploring direct current (DC) microgrids in traditional power grids. A key challenge in operating these microgrids is ensuring proper current distribution among converters. While conventional droop control has been used to address this issue, it requires compensating for voltage deviations in the DC bus. This paper introduces an innovative distributed secondary control approach that effectively addresses both voltage restoration and current sharing challenges within a standalone DC microgrid. The distributed secondary control proposed in this study is integrated into the microgrid’s cyber layer, enabling information sharing between controllers. This distributed approach ensures reliability, even in the event of partial communication connection failures. The controller employs a fuzzy logic control approach to dynamically determine the parameters of the secondary control, resulting in an enhanced control response. Additionally, the proposed approach can handle constant power and resistive loads without specific requirements. Employing the Lyapunov method, we have derived adequate stability conditions for the proposed controller. The performance of the controller has been assessed using MATLAB/Simulink® models and validated with real-time experimental testing performed with a SpeedgoatTM real-time machine, considering five different test cases. The results indicated that the proposed control system is robust in achieving its control objectives within a DC microgrid, exhibiting fast response and minimal oscillations.

Heuristic control of nonlinear power systems: Application to the infinite bus problem

Heuristic control of nonlinear power systems: Application to the infinite bus problem

User grouping and resource management in efficient NOMA‐OMA transmission scheme for infotainment message dissemination in VANETs

AbstractThe data distribution for infotainment services at vehicular ad‐hoc networks (VANETs) has become a research hotspot in recent years. Non‐orthogonal multiple access (NOMA) is accepted as an enabling technology for 5G and beyond due to its improved spectral efficiency. In this work, we consider a VANET communication scenario where users have common data demands such as high‐density maps, local entertainment/shopping options or other popular media content. For such a scenario, we propose an efficient clustering scheme together with a hybrid NOMA‐OMA scheme for improved spectral and power efficiency. For this setup, we also develop an optimal bandwidth allocation strategy to improve the power efficiency further. We formulate a one dimensional nonlinear power minimization problem such that the bandwidth allocation for the system can be optimized. The complexity and optimality analysis of optimization algorithms used for power minimization are performed. The improved performance of the proposed scheme in terms of power efficiency, spectral efficiency and latency performance is showcased in comparison to conventional NOMA and OMA approaches.

Faulty phase identification and ground detection in TCSC compensated lines integrated with wind farms

Nowadays there is a trend for offshore wind farms to be connected with power grids through a TCSC series controlled compensating device employed in transmission lines for the improvement of large power flows. In such transmission lines, faulty phase identification and ground detection create a challenge for conventional distance relaying schemes because of non-linear output power fluctuation due to variations in wind speed and different firing angle operations of TCSC. Therefore, to overcome the problem of such transmission lines relaying, a novel time-frequency analysis-based intrinsic time scale decomposition (ITD) method is proposed in this paper. The proposed intrinsic time scale decomposition method uses only a three-phase grid side current from relaying end for faulty phase and ground detection and ITD supported random forest classifier for fault classification accuracy approach. The evaluation of the proposed scheme is tested on several fault cases with varying system parameters and non-fault transient events through the EMTDC/PSCAD platform during different wind speeds and varying firing angle operations of TCSC. The performance of the proposed scheme is also verified through a real-time interface dSPACE DS 1104 control prototype hardware. Finally, a comparison analysis with existing techniques demonstrated the effectiveness of the presented method to assess the mentioned problem of the conventional protective relaying schemes. The proposed method demonstrated a 100% accuracy for faulty phase selection and a 99.99% accuracy for fault classification.

Robust integral backstepping control microgrid connected photovoltaic System with battery energy storage through multi-functional voltage source inverter using direct power control SVM strategies

This paper proposes a robust control based on the integral backstepping control (IBC) for power quality enhancement of micro-grid-connected photovoltaic (PV) system with battery energy storage systems (BESS), The DC side consists of a PV system and battery storage. As for the AC side, it consists of three phases of a multi-functional two-level voltage source inverter (MVSI) coupled to the electrical grid via an inductive filter, all feeding a non-linear load. The MVSI is controlled by a nonlinear direct power control (DPC) strategy with space vector modulation (SVM) and the proposed IBC technique. Using the proposed IBC technique to control the voltage of the DC link voltage loop, the active/reactive power loops of the grid, the compensation of the harmonic currents of the network, and the injection of the power of the PV battery into the grid, loop of the maximum power point tracking (MPPT) regardless of the random nature of weather changes and guarantees optimal power management system battery storage. Using simulation under the MATLAB environment, the proposed control system was validated and compared to the conventional strategies (proportional–integral controller and backstepping controller) in terms of success, performance, robustness, and efficiency. In addition to its ability to respond under any irradiation distortion and non-linear load unbalance.

Depression Detection Based on Analysis of EEG Signals in Multi Brain Regions.

As an objective method to detect the neural electrical activity of the brain, electroencephalography (EEG) has been successfully applied to detect major depressive disorder (MDD). However, the performance of the detection algorithm is directly affected by the selection of EEG channels and brain regions. To solve the aforementioned problems, nonlinear feature Lempel-Ziv complexity (LZC) and frequency domain feature power spectral density (PSD) were extracted to analyze the EEG signals. Additionally, effects of different brain regions and region combinations on detecting MDD were studied with eyes closed and opened in a resting state. The mean LZC of patients with MDD was higher than that of the control group, and the mean PSD of patients with MDD was generally lower than that of the control group. The temporal region is the best brain region for MDD detection with a detection accuracy of 87.4%. The best multi brain regions combination had a detection accuracy of 92.4% and was made up of the frontal, temporal, and central brain regions. This paper validates the effectiveness of multiple brain regions in detecting MDD. It provides new ideas for exploring the pathology of MDD and innovative methods of diagnosis and treatment.

Design of Total Harmonic Distortion Reduction Using Quantum Coyote Optimization Algorithm for Hybrid Power Generation Systems

The usage of various inverters in various industries has gained considerable attention in the power electronics industry in recent years. The harmonic distortion that is induced by various renewable energy sources, along with the growing use of nonlinear loads and power electronic devices, has a significant impact on the distribution system. This is because of the rise in penetration of various renewable energy sources and the usage of nonlinear loads and power electronic devices. In addition, distributed generation (DG) units with inverters (such as solar (PV) and wind turbines) that are integrated into distribution networks are viewed as significant harmonic producers that have substantial adverse effects on power quality. The power quality in the system suffers because of these generators. This study proposes a method of harmonic mitigation for addressing power quality problems that are present in distribution systems as a solution to the challenges that have been found. These concerns have been brought to light as a result of previous research. The standard two-level and three-level inverters were the basis for the development of the multilevel inverter (MLI), which was meant to address their shortcomings. One of the effective technologies that can maintain constant performance is the hybrid power generating system. A hybrid energy system has several benefits, including high dependability, cheap cost and minimal emissions. When used in a hybrid power production system, the reduction of total harmonic distortion (THD) becomes absolutely necessary (HPGS). In this context, the research provides a novel approach for high-performance quantum computing called quantum coyote optimization algorithm-based THD reduction (QCOA-THDR). The QCOA-THDR approach that has been presented has been tested with several converters, including SEPIC, buck–boost and Cuk converters. Additionally, the proportional as well as the integral gain variables of the proportional integral (PI) controller are set in order to achieve decreased total harmonic distortion (THD). In addition, the QCOA system is formed by combining the ideas of quantum computing (QC) with the traditional COA. This is how the QCOA system comes to exist. A limited number of simulations were run, and the results are being analyzed from a variety of perspectives in order to investigate the improved effects that the QCOA-THDR approach has on data. The QCOA-THDR method was shown to have superior results than the more modern techniques, as shown by the comparison research.

Development of mathematical models to predict the load-carrying capacity of tractor tires on rigid surface

Objective: The objective of this study was to develop the load-carrying capacity models of tractor tires on the rigid surface for both, radial and bias tires. Material and Methods: In order to develop functions, two tire constructional variables (section width and overall diameter), inflation pressure, and forward speed for the load-carrying capacity model were considered. The models developed in the literature for the load-carrying capacity of tires on rigid and soil surfaces were built on some limited data and as a result of this, the predominant variable and contribution of other variables still remain unknown. This study has the widest range of tractor tire sizes (width and diameter). The load-carrying capacity models developed in this study were verified with the theoretical models and experimental measurement values in the literature. Results: As a result of the study, it was found that the appropriate mathematical models were in non-linear (power) form and the coefficient of determination of the models was greater than 0.95. Conclusion: The models were verified against published data in the literature and found that the predictions from the models are in good agreement with the measured values.

Asymmetric majority pillage games

We study pillage games (Jordan in J Econ Theory 131(1):26–44, 2006), which model unstructured power contests. To enable empirical tests of pillage game theory, we relax a symmetry assumption that agents’ intrinsic contributions to a coalition’s power is identical. We characterise the core for all n. In the three-agent game: (i) only eight configurations are possible for the core, which contains at most six allocations; (ii) for each core configuration, the stable set is either unique or fails to exist; (iii) the linear power function creates a tension between a stable set’s existence and the interiority of its allocations, so that only special cases contain strictly interior allocations. Our analysis suggests that non-linear power functions may offer better empirical tests of pillage game theory.