PV panel modeling and identification

In this chapter, the modelling techniques of PV panels from I-V characteristics are discussed. At the beginning, a necessary review on the various methods are presented, where difficulties in mathematics, drawbacks in accuracy, and challenges in implementation are highlighted. Next, a novel approach based on linear system identification is demonstrated in detail. Other than the prevailing methods of using approximation (analytical methods), iterative searching (classical optimization), or soft computing (artificial intelligence), the proposed method regards the PV diode model as the equivalent output of a dynamic system, so the diode model parameters can be linked to the transfer function coefficients of the same dynamic system. In this way, the problem of solving PV model parameters is equivalently converted to system identification in control theory, which can be perfectly solved by a simple integral-based linear least square method. Graphical meanings of the proposed method are illustrated to help readers understand the underlying principles. As compared to other methods, the proposed one has the following benefits: 1) unique solution; 2) no iterative or global searching; 3) easy to implement (linear least square); 4) accuracy; 5) extendable to multi-diode models. The effectiveness of the proposed method has been verified by indoor and outdoor PV module testing results. In addition, possible applications of the proposed method are discussed like online PV monitoring and diagnostics, noncontact measurement of POA irradiance and cell temperature, fast model identification for satellite PV panels, and etc

Nonlinear wave-particle resonance in deterministic and stochastic kinetic plasmas

In kinetic plasma physics, BGK modes are ubiquitous solutions to the Vlasov equation, with particles travelling along orbits where the single particle energy is conserved. Approximate extensions of these exact solutions have been successfully used in the past to understand the formation and evolution of ‘holes’ and ‘clumps’, coherent structures on the particle distribution function which under certain conditions form in the nonlinear phase of the evolution of kinetic plasmas. In this thesis, analytical results are shown which consider perturbations and deformations to BGK orbits, allowing one to robustly construct more exotic orbits that allow for mode growth and frequency chirping. Computational results produced using the DARK code are presented, examining stochastic and deterministic populations in a 1D electrostatic plasma, and how they affect electrostatic waves exhibiting Landau resonance, based on Berk-Breizman models. A model is presented for parametric mode-mode destabilisation via holes and clumps interacting via the background distribution. Finally, work using the machine learning framework ERICSON is presented, analysing frequency spectrograms of magnetic perturbations in Alfvénic and sub-Alfvénic frequency ranges

Closed-Form Solution of Radial Transport of Tracers in Porous Media Influenced by Linear Drift

The authors thank Olakunle Popoola and Ofomana Emmanuel for useful discussions of this topic.Peer reviewedPublisher PD

Topological Phenomena in the Real Periodic Sine-Gordon Theory

The set of real finite-gap Sine-Gordon solutions corresponding to a fixed spectral curve consists of several connected components. A simple explicit description of these components obtained by the authors recently is used to study the consequences of this property. In particular this description allows to calculate the topological charge of solutions (the averaging of the $x$-derivative of the potential) and to show that the averaging of other standard conservation laws is the same for all components.Comment: LaTeX, 18 pages, 3 figure

Experimental data-driven reduced-order modeling of nonlinear vertical sloshing for aeroelastic analyses

This thesis focuses specifically on the study of nonlinear sloshing effects caused by large tank motions in a direction perpendicular to the free liquid surface with emphasis on aeronautical applications. Sloshing is a phenomenon that typically occurs in aircraft tanks as they are subjected to loads caused by gusts, turbulence and landing impacts. This type of sloshing leads to a noticeable increase in overall structural damping, yet it is generally not modeled in the design phase of modern aircraft. The identification and study of such dissipative effects may enable the development of less conservative aircraft configurations in the future, allowing for increasingly lighter structures and reduced environmental impact. The present thesis proposes a combined experimental and numerical approach aimed at obtaining reduced-order models for vertical sloshing, to be subsequently integrated into aeroelastic modeling and applications for the assessment of their effects on overall performance. An experimental campaign is first carried out to characterise the nonlinear dissipative behaviour of vertical sloshing for different filling levels. Specifically, a controlled electrodynamic shaker is employed to provide vertical displacement by means of sine-sweep excitation. By exploiting vertical harmonic motion, it is shown how the frequency and amplitude of the imposed excitation significantly influence the dissipative capabilities of the sloshing liquid. The same experiment is used to create a database - with an acquisition phase that considers vertical sloshing as an isolated system - to build a neural-network-based reduced-order model. The dynamics to be modeled is considered as a black box process, leading to the identification of a surrogate model driven only by input/output signals, regardless the knowledge of the internal dynamics. In order to assess the capability of the identified reduced order model for sloshing, the same tank used to generate the training data is mounted at the free end of a cantilever beam to create a new experimental setup in which a fluid-structure interaction scenario is expected. Indeed, this experiment provides experimental data for the validation of the identified dynamic model by comparison with numerical data. The comparison is carried out using a dynamic virtual simulation model corresponding to the experiment, in which the numerical model of the beam interacts with the reduced-order model simulating the sloshing dynamics. Finally, the experimentally validated reduced-order model is used in two different aeroelastic applications - wing prototype and flying wing model - to finally predict the dissipative effects induced by vertical sloshing on the aeroelastic response. Aeroelastic response analyses under pre- and post-critical conditions showed how the vertical sloshing dynamics helps to alleviate the dynamic loads due to severe gusts while providing limit cycle oscillation beyond the flutter margin

Domain-growth-induced patterning for reaction-diffusion systems with linear cross-diffusion

In this article we present, for the first time, domain-growth induced pat- tern formation for reaction-diffusion systems with linear cross-diffusion on evolving domains and surfaces. Our major contribution is that by selecting parameter values from spaces induced by domain and surface evolution, patterns emerge only when domain growth is present. Such patterns do not exist in the absence of domain and surface evolution. In order to compute these domain-induced parameter spaces, linear stability theory is employed to establish the necessary conditions for domain- growth induced cross-diffusion-driven instability for reaction-diffusion systems with linear cross-diffusion. Model reaction-kinetic parameter values are then identified from parameter spaces induced by domain-growth only; these exist outside the classical standard Turing space on stationary domains and surfaces. To exhibit these patterns we employ the finite element method for solving reaction-diffusion systems with cross-diffusion on continuously evolving domains and surfaces