maximum power point tracking in photovoltaic systems using model reference adaptive control

This thesis proposes adaptive control architecture for maximum power point tracking (MPPT) in photovoltaic systems. Photovoltaic systems provide promising ways to generate clean electric power. MPPT technologies have been used in photovoltaic systems to deliver the maximum power output to the load under changes of solar insolation and solar panel's temperature. To improve the performance of MPPT, this thesis proposes a two-layer adaptive control architecture that can effectively handle the uncertainties and perturbations in the photovoltaic systems and the environment. The first layer of control is ripple correlation control (RCC), and the second layer is model reference adaptive control (MRAC). By decoupling these two control algorithms, the control system achieves the maximum power point tracking with shorter time constants and overall system stability. To track the maximum power point as the solar insolation changes, the RCC algorithm computes the corresponding duty cycle, which serves as the input to the MRAC layer. Then the MRAC algorithm compensates the under-damped characteristics of the power conversion system: the original transfer function of the power conversion system has time-varying parameters, and its step response contains oscillatory transients that vanish slowly. Using the Lyapunov approach, an adaption law of the controller is derived for the MRAC system to eliminate the under-damped modes in power conversion

Adaptive Control for Solar Energy Based DC Microgrid System Development

During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)’s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed

Using risk data as a source for human reliability assessment during shipping LNG offloading work

This manuscript has been made open access under a Creative Commons Attribution (CC BY) licence under the terms of the University of Aberdeen Research Publications Policy. https://creativecommons.org/licenses/by/4.0/Peer reviewe

A neural network-based adaptive power-sharing strategy for hybrid frame inverters in a microgrid

The capacitive-coupling inverter (CCI) is more cost-effective in reactive power conditioning and enhanced reactive power regulation ability when compared with the inductive-coupling inverter (ICI). As power conditioning capability is vital for a microgrid (MG) system, a new MG frame with hybrid parallel-connected ICIs and CCIs was proposed in this paper. With lower DC-link voltage for the CCI, an adaptive power sharing method was proposed for reducing total rated power and losses. A power-sharing control layer based on a back-propagation neural network that guarantees rapid and accurate sharing ratio computation was investigated as well. The results of simulations and experiments were used to verify the effectiveness of the proposed method

Emission of PAHs, NPAHs and OPAHs from residential honeycomb coal briquette combustion

Coal combustion is one of the most significant sources of air pollution in China. In this study, emission factors (EFs) of 15 polycyclic aromatic hydrocarbons (PAHs), 26 nitrated PAHs (NPAHs) and 6 oxygenated PAHs (OPAHs) were determined in five different coals with different geological maturity (vitrinite reflectance <i>R</i>_O = 0.77–1.88%) burned in the form of honeycomb briquettes. The total EFs ranged from 9.82 to 215 mg kg^–1 for PAHs, 0.14 to 1.88 mg kg^–1 for NPAHs and 4.47 to 20.8 mg kg^–1 for OPAHs. Measured EFs and gas-particle partitioning varied depending on the geological maturity. The lowest EFs were found in anthracite. The proportion of PAHs, NPAHs and OPAHs in gaseous phase increasing with increased geological maturity. The coal with higher geological maturity produced more 3-ring PAHs. On the basis of the statistical analysis for the residential sector of China in 2008, PAHs, NPAHs and OPAHs emitted from residential honeycomb coal briquettes were 4.36 Gg, 0.03 Gg and 0.47 Gg in 2007, respectively. By 2020, the emission would decrease to 2.18 Gg, 0.02 Gg and 0.24 Gg for PAHs, NPAHs and OPAHs due to the increasing usage of new energy resources. If only anthracite is used as the residential coal, 93% PAHs, 87% NPAHs and 71% OPAHs would be reduced in 2020

Impact of in-cloud aqueous processes on the chemical compositions and morphology of individual atmospheric aerosols

The composition, morphology, and mixing structure of individual cloud residues (RES) and interstitial particles (INT) at a mountaintop site were investigated. Eight types of particles were identified, including sulfate-rich (S-rich), S-organic matter (OM), aged soot, aged mineral dust, aged fly ash, aged metal, refractory, and aged refractory mixture. A shift of dominant particle types from S-rich (29 %) and aged soot (27 %) in the INT to aged refractory mixture (23 %) and S-OM (22 %) in the RES is observed. In particular, particles with organic shells are enriched in the RES (27 %) relative to the INT (12 %). Our results highlight that the formation of more oxidized organic matter in the cloud contributes to the existence of organic shells after cloud processing. The fractal dimension (D$_{f}$), a morphologic parameter to represent the branching degree of particles, for soot particles in the RES (1.82 ± 0.12) is lower than that in the INT (2.11 ± 0.09), which indicates that in-cloud processes may result in less compact soot. This research emphasizes the role of in-cloud processes in the chemistry and microphysical properties of individual particles. Given that organic coatings may determine the particle hygroscopicity, activation ability, and heterogeneous chemical reactivity, the increase of OM-shelled particles upon in-cloud processes should have considerable implications

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Shape-Controlled Synthesis of Palladium-Copper Nanoalloys with Improved Catalytic Activity for Ethanol Electrooxidation

A facile solvothermal strategy is developed for the preparation of nanometer sized Pd-Cu alloy. We can control the morphology of these alloys with the use of ethylene glycol (EG) in the presence of KOH. Namely, by increasing the concentration of KOH/EG, the Pd-Cu alloys with different morphologies from near-spherical nanoparticles (NPs) to nanorods and nanowire networks have been prepared. Among all these alloys, near-spherical Pd-Cu NPs-modified electrodes exhibit the highest catalytic activity (11.7 mA/cm2) and stability toward the electrooxidation of ethanol in comparison with commercial Pd/C-modified ones (2.1 mA/cm2)

On the Communication Performance of Airborne Distributed Coherent Radar

Compared with a monostatic radar, airborne distributed coherent radar (ADCR) has been widely applied thanks to its flexibility, greater degree of freedom, stronger detection, and anti-jamming ability. Unlike distributed ground-based radar, the precondition for ADCR to perform tasks is maintenance of stable wireless communication links among the unmanned aerial vehicles (UAVs). Therefore, the communication channel modeling of ADCR is very important. This paper mainly analyzes the performance of a communication system composed of radar UAVs, communication UAV (relay), and ground base station. The probability density function (PDF) and outage probability (OP) of signal-to-noise ratio (SNR) at the ground terminal are derived analytically in the cases of transmission power error, UAV position error, and multi-path fading. Numerical simulation shows the validity of the derived results