Power System Control with an Embedded Neural Network in Hybrid System Modeling

The output limits of the power system stabilizer (PSS) can improve the system damping performance immediately following a large disturbance. Due to non-smooth nonlinearities from the saturation limits, these values cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures can been used. A feedforward neural network (FFNN) (with a structure of multilayer perceptron neural network) is applied to identify the dynamics of an objective function formed by the states, and thereafter to compute the gradients required in the nonlinear parameter optimization. Moreover, its derivative information is used to replace that obtained from the trajectory sensitivities based on the hybrid system model with the differential-algebraic-impulsive-switched (DAIS) structure. The optimal output limits of the PSS tuned by the proposed method are evaluated by time-domain simulation in both a single machine infinite bus system (SMIB) and a multi-machine power system (MMPS)

Parameter Optimization of PSS Based on Estimated Hessian Matrix from Trajectory Sensitivities

This paper describes the optimal tuning for the output limits of the power system stabilizer (PSS), which can improve the system damping performance immediately following a large disturbance. The non-smooth nonlinear parameters such as the saturation limits of the PSS cannot be tuned by the conventional methods based on linear approaches. To implement the systematic optimal tuning for the output limits of the PSS, a feedforward neural network (FFNN) is applied to the hybrid system model based on the differential-algebraic-impulsive-switched (DAIS) structure. The FFNN is firstly designed to identify the trajectory sensitivities obtained from the DAIS structure. Thereafter, it estimates the second-order derivatives of an objective function J, which is used during iterations of optimization process. The performance of the optimal output limits tuned by the proposed method is evaluated by applying a large disturbance to a power system

Power System Control with an Embedded Neural Network in Hybrid System Modeling

Output limits of the power system stabilizer (PSS) can improve the system damping performance immediately following a large disturbance. Due to nonsmooth nonlinearities arising from the saturation limits, these values cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures can been used. A feedforward neural network (with a structure of multilayer perceptron neural network) is applied to identify the dynamics of an objective function formed by the states and, thereafter, to compute the gradients required in the nonlinear parameter optimization. Moreover, its derivative information is used to replace that obtained from the trajectory sensitivities based on the hybrid system model with the differential-algebraic-impulsive-switched structure. The optimal output limits of the PSS tuned by the proposed method are evaluated by time-domain simulation in both a single-machine infinite bus system and a multimachine power system

Heterologous expression of a tannic acid-inducible laccase3 of Cryphonectria parasitica in Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>A tannic acid-inducible and mycoviral-regulated laccase3 (<it>lac</it>3) from the chestnut blight fungus <it>Cryphonectria parasitica </it>has recently been identified, but further characterization was hampered because of the precipitation of protein products by tannic acid supplementation. The present study investigated the heterologous expression of the functional laccase3 using a yeast <it>Saccharomyces cerevisiae</it>.</p> <p>Results</p> <p>Laccase activity in the culture broth of transformants measured using a laccase-specific substrate suggested that the <it>lac</it>3 gene was successfully expressed and the corresponding protein product secreted into the culture media. In addition, activity staining and Western blot analysis of a native gel revealed that the enzyme activity co-existed with the protein product specific to anti-laccase3 antibody, confirming that the cloned <it>lac</it>3 gene is responsible for the laccase activity. When transformants were grown on plates containing tannic acid-supplemented media, brown coloration was observed around transformed cells, indicating the oxidation of tannic acid. However, the enzymatic activity was measurable only in the selective ura^-media and was negligible in nonselective nutrient-rich culture conditions. This was in part because of the increased plasmid instability in the nonselective media. Moreover, the protein product of <it>lac</it>3 appears to be sensitive to the cultured nonselective nutrient-rich broth, because a rapid decline in enzymatic activity was observed when the cultured broth of ura^-media was mixed with that of nonselective nutrient-rich broth. In addition, constitutive expression of the <it>lac</it>3 gene resulted in a reduced cell number of the <it>lac</it>3 transformants compared to that of vector-only transformed control. However, the presence of recombinant vector without <it>lac</it>3 induction did not affect the growth of transformants.</p> <p>Conclusions</p> <p>The results suggest that expression of the <it>lac</it>3 gene has an inhibitory effect on the growth of transformed <it>S. cerevisiae </it>and that the controlled expression of <it>lac</it>3 is appropriate for the possible application of recombinant yeast to the treatment of phenolic compounds.</p

Stability of hydrogenation states of graphene and conditions for hydrogen spillover

The hydrogen spillover mechanism has been discussed in the field of hydrogen storage and is believed to have particular advantage over the storage as metal or chemical hydrides. We investigate conditions for practicality realizing the hydrogen spillover mechanism onto carbon surfaces, using first-principles methods. Our results show that contrary to common belief, types of hydrogenation configurations of graphene (the aggregated all-paired configurations) can satisfy the thermodynamic requirement for room-temperature hydrogen storage. However, the peculiarity of the paired adsorption modes gives rise to a large kinetic barrier against hydrogen migration and desorption. It means that an extremely high pressure is required to induce the migration-derived hydrogenation. However, if mobile catalytic particles are present inside the graphitic interstitials, hydrogen migration channels can open and the spillover phenomena can be realized. We suggest a molecular model for such a mobile catalyst which can exchange hydrogen atoms with the wall of graphene.open151

Batalin-Tyutin Quantization of the Chiral Schwinger Model

We quantize the chiral Schwinger Model by using the Batalin-Tyutin formalism. We show that one can systematically construct the first class constraints and the desired involutive Hamiltonian, which naturally generates all secondary constraints. For $a>1$, this Hamiltonian gives the gauge invariant Lagrangian including the well-known Wess-Zumino terms, while for $a=1$ the corresponding Lagrangian has the additional new type of the Wess-Zumino terms, which are irrelevant to the gauge symmetry.Comment: 15 pages, latex, no figures, to be published in Z. Phys. C (1995

Synergistic effect of Indium and Gallium co-doping on growth behavior and physical properties of hydrothermally grown ZnO nanorods

We synthesized ZnO nanorods (NRs) using simple hydrothermal method, with the simultaneous incorporation of gallium (Ga) and indium (In), in addition, investigated the co-doping effect on the morphology, microstructure, electronic structure, and electrical/optical properties. The growth behavior of the doped NRs was affected by the nuclei density and polarity of the (001) plane. The c-axis parameter of the co-doped NRs was similar to that of undoped NRs due to the compensated lattice distortion caused by the presence of dopants that are both larger (In3+) and smaller (Ga3+) than the host Zn2+ cations. Red shifts in the ultraviolet emission peaks were observed in all doped NRs, owing to the combined effects of NR size, band gap renormalization, and the presence of stacking faults created by the dopant-induced lattice distortions. In addition, the NR/p-GaN diodes using co-doped NRs exhibited superior electrical conductivity compared to the other specimens due to the increase in the charge carrier density of NRs and the relatively large effective contact area of (001) planes. The simultaneous doping of In and Ga is therefore anticipated to provide a broader range of optical, physical, and electrical properties of ZnO NRs for a variety of opto-electronic applications