Fuzzy logic switching of thyristor controlled braking resistorconsidering coordination with SVC

This paper presents a new switching control scheme for braking resistors (BR) using fuzzy logic to enhance overall stability of electric power systems. In addition, the coordination with an SVC is also considered to achieve a wider stable region. The braking resistor is set on one of the generator busbars, where the real power output from the generator is measured to determine the firing-angle of the thyristor switch. The switching control scheme is simple so as not to require heavy computation on the microcomputer based switching controller. An SVC is set on one of the busbars in the system. The switching of the SVC uses a similar fuzzy logic control scheme to the one for the BR. Simulation results show the effectiveness of the proposed fuzzy logic switching control scheme     

Evaluation of advanced fuzzy logic PSS on analog network simulatorand actual installation on hydro generators

This paper presents the experimental evaluation of an advanced fuzzy logic PSS on the analog network simulator at the Research Laboratory of Kyushu Electric Power Co., Inc. The proposed power system stabilizer (PSS) is set up by using a personal computer with A/D and D/A conversion interfaces. The personal computer based PSS was set on the analog network simulator to evaluate the effectiveness of the advanced fuzzy logic control scheme, and to provide sufficient data for the actual installation of the proposed PSS on hydro-units in the Kyushu Electric Power System. This paper also describes the actual installation of the proposed PSS on hydro-units in the Kyushu Electric Power System for the long term evaluation of the proposed PSS using its prototypes     

Scaling of land surface temperature using satellite data: A case examination on ASTER and MODIS products over a heterogeneous terrain area

Land surface temperature (LST) is a key parameter in numerous environmental studies. Surface heterogeneity induces uncertainty in pixel-wise LST. Spatial scaling may account for the uncertainty, however, different approaches lead to differences in scaled values. Satellite-retrieved LST may be representative of the pixel-wise LST and useful for scaling analysis, but the limited accuracy of retrieved values adds uncertainty into the scaled values. Based on the Stefan-Boltzmann (S-B) law, this study proposed scaling approaches for LST over flat and relief areas to explore the combined uncertainties in scaling using satellite-retrieved data. To take advantage of simultaneous, multi-resolution observations at coincident nadirs by the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and the MODerate-resolution Imaging Spectroradiometer (MODIS), LST products from these two sensors were examined for part of the Loess Plateau in China. 90-m ASTER LST data were scaled up to 1 km using the proposed approaches, and variation in the LST was generally reduced after scaling. Amongst the sources of uncertainties, surface heterogeneity (emissivity) and different scaling approaches resulted in very minor differences, with a maximum difference of 0.2 K for the upscaled LST. Terrain features, taken as an areal weighting factor, had negligible effects on the upscaled value. Limited accuracy of the retrieved LST was the major uncertainty. The overall LST increased 0.6 K on average with correction for terrain-induced angular effect and 0.4 K for both angular and adjacency effects over the study area. Accounting for terrain correction in scaling is necessary for rugged areas. With terrain correction, the upscaled ASTER LST achieved an agreement of − 0.1 ± 1.87 K and a root mean square error (RMSE) of 1.87 K overall with the 1-km MODIS LST rectified by Wan et al.'s approach [Wan, Z., Zhang, Y., Zhang Q., Li, Z.-L. (2002b), Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83, 163-180]. Refining the rectification approach resulted in a better agreement of − 0.2 ± 1.57 K and a RMSE of 1.58 K.     

Structural analysis of Pareto-optimal solution sets for multi-objective optimization: An application to outer window design problems using Multiple Objective Genetic Algorithms

In single-objective optimization problems, with only one optimal design objective, the absolute optimal solution to maximize/minimize the objective function can be determined. However, in most real design problems, the optimization problems are multi-objective, where two or more independent design objectives must be optimized simultaneously, and no single absolute optimal solution necessarily exists. In these cases, it is helpful for designers to recognize the range of alternative solutions that exist in Pareto-optimal sets and choose an acceptable solution from among them. In this paper, the authors carried out multi-objective optimization using Multiple Objective Genetic Algorithms through a real case study involved in indoor environmental design – the design of outer windows. Then the authors analyzed structure of Pareto-optimal solution sets. Here we present the analysis process as well as the case study details, and show how the method proposed here is effective at finding an acceptable solution for multi-objective optimization problems.     

Optimization of variables in air conditioning control systems: Applications of simulations integrating CFD analysis and response factor method

The integration of three-dimensional spatial distributions into building simulations is of significant interest, and computational fluid dynamics (CFD) analysis is widely employed in building design processes. For example, based on the experience of architects and engineers, CFD analyses are often conducted under steady boundary conditions to determine the degree of attainment of indoor environments. However, CFD analyses have large calculation costs and cannot be often used for simulations with unsteady boundary conditions such as energy simulations in the building design processes. Thus, we developed a method that calculates sensitivities from heat sources to an arbitrary point in an indoor environment and integrates them into simulations with unsteady boundary conditions. In the proposed method, CFD analysis is employed under steady boundary conditions to calculate the response factors, and the resulting sensitivities are integrated into simulations under unsteady boundary conditions. In the present study, the proposed method was applied to optimize the variables of an air conditioning control system. With our method, temperature changes at a sensor over time are calculated from the time series of air supply temperature. In total, 800 calculations were conducted, and the optimal variables that allow the temperature at the sensor to reach the target value quickly were obtained. Except for the time required to calculate the response factors, the optimization in the present study took only a few seconds. If only CFD analysis was used for the optimization, the calculations would take a year. Thus, calculating the sensitivities via CFD analysis and utilizing the results in simulations is a useful approach for solving optimization problems. Moreover, the proposed method is applicable to simulations that require three-dimensional spatial distributions to enhance the accuracy of the calculation such as energy simulations.     

Development of an optimal design aid system based on building information modeling

This study proposes an optimal building design aid system that integrates computer aided design (CAD), building environmental simulation tools and an optimization algorithm, based on the concept of building information modeling (BIM). BIM is a process of generating and managing data during a building’s life cycle. It can be used to demonstrate the entire building’s life cycle, including its construction and operation. Because the design of a build may vary from an abstract shape to precise details, the building’s database should vary accordingly. To store, manage and utilize the building’s data efficiently, we suggest an evolving database structure for our design aid system. A case study verifies that the system can acquire data from CAD, run a number of simulations and generate Pareto solutions automatically during several design stages.     

In situ mRNA hybridization technique for analysis of human telomerase RNA in gastric precancerous and cancerous lesions

Telomerase, the ribonucleoprotein enzyme that elongates telomerase, is repressed in normal somatic cells but is reactivated during tumor progression. The purpose of this study was to investigate the localization of human telomerase RNA (hTR) expression in human gastric precancerous and cancerous lesions by using in situ mRNA hybridization (ISH) with avidin-biotin staining. We also examined telomerase activity in these lesions by using hybridization protection assay connected with a telomeric repeat amplification protocol (TRAP/HPA). Analyzed tissue samples were as follows; 132 cases of chronic atrophic gastritis without intestinal metaplasia, 115 incomplete-type intestinal metaplasias, 40 complete-type intestinal metaplasias, 23 hyperplastic polyps, 23 tubular adenomas and 26 adenocarcinomas. In ISH analysis, high levels of hTR expression were observed preferentially in the nuclei at the single-cell level. hTR-expressing cells in carcinomas and adenomas were significantly more frequent than those of the other lesions (P < 0.001). The expression pattern of hTR in carcinoma and adenoma tissues was heterogeneous and similar intratumor heterogeneity was detected in Ki-67 immunoreactivity. Infiltrating lymphocytes in tissue also exhibited high levels of hTR expression. In TRAP/HPA analysis, carcinomas had significantly more frequent positivity for telomerase activity and a higher level of telomerase activity than the other lesions (P < 0.05). However, the amount of telomerase activity did not parallel the expression level of hTR. Our data suggest that hTR expression increases in the early stages of stomach carcinogenesis and that sufficient synthesis of hTR is a prerequisite for telomerase reactivation in tumorigenesis.     

Real time control of micro-machine system using micro-computerbased fuzzy logic power system stabilizer

A microcomputer based fuzzy logic power system stabilizer is applied to a micro-machine system to investigate its efficiency in real time control. The stabilizing signal is determined by using measured speed or real power signals at every sampling time to damp the system oscillations. The results show the proposed stabilizer improves the system damping effectively subject to various types of disturbances     

Identification of optimal operating point of PV modules usingneural network for real time maximum power tracking control

This paper presents an application of a neural network for the identification of the optimal operating point of PV modules for the real time maximum power tracking control. The output power from the modules depends on the environmental factors such as insolation, cell temperature, and so on. Therefore, accurate identification of optimal operating point and real time continuous control are required to achieve the maximum output efficiency. The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also a highly accurate estimation of the maximum power from the PV modules