Anant Oonsivilai

Appliance of recurrent neural network toward distance transmission lines protection

To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of recurrent neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the realtime purposes.

Identification of critical measurements in the power system network

The main objective of this research work is to obtain the minimum number of measurements and their weights (index) in the power system network. The use of singular value decomposition (SVD) is used to find a simpler approximation that speed up the search dramatically. The SVD is used to solve the problem of minimum number of measurements placement while maintaining accuracy as well as network observability. In this paper, the weights (index) of the measurements are obtained by their effect measured by the respective relative error in state estimation. The critical and non critical measurements are identified in the system.

SOLVING THE UNIT COMMITMENT PROBLEM USING AN ADAPTIVE IMMUNE GENETIC ALGORITHM

This paper presents an Adaptive Immune Genetic Algorithm (AIGA) solution to solve the Unit Commitment (UC) problem. The unit commitment problem formulation takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as the minimization of the total objective function while satisfying all the associated constraints. Mathematical formulation, illustration and production results for a 10 generator‐scheduling problem are presented. Finally, numerical results of systems are established the effectiveness of purpose technique.

Measurement loss effect on power system state estimation

The main objective of this research work is to classify measurements units in optimal measurement environments in the power system network. Firstly, the use of singular value decomposition is used to find the optimal measurements placement. This is the optimum environment where each measurement unit is given weight upon its effect on the state estimation accuracy. Loss of the measurement unit can be due to the bad data received and the measurement is discarded or not telemetered due to the communication link error. In this case the respective relative error in state estimation is obtained by using MATLAB simulation. The higher weighted as considered to be critical and less weighted are considered non critical measurements are identified in the power system. In this paper related quantities that are more affected are identified.

Effect of Heat Treatment on Aging Degradation of the Piezoelectric Properties of Lead Zirconate Titanate

The aging degradation of the piezoelectric properties of lead zirconate titanate (PZT) was investigated at different heat treatment temperatures (30 to 80% of Curie temperature (TC)). The aging degradation behavior was represented by the decrease of piezoelectric charge coefficient (d33 ) and electromechanical coupling factor (k). The results showed that the degree of aging degradation of piezoelectric properties increased with increasing heat treatment temperature. The aging degradation was more pronounced when the heat treatment temperature was greater than 50% of TC. These results can be applied to predict the aging rate of electronic devices containing a PZT component.

Silk Texture Defect Recognition System Using Computer Vision and Artificial Neural Networks

Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION

State estimation using extended SEMM in power system

In this paper, power system state estimator (SE) solution using extended state estimation matrix measurements (SEMM) is presented. Within an optimum measurement placement environment, the extended SEMM is formed to enhance the state estimator solution in accuracy. The main idea is to maintain the readings from available measurement units to extend the new SEMM. This is determined by using the correlation and/or regression analysis of the new measurements and the available measurements. Absolute voltage error is used to analyze the system performance for IEEE 14-bus and IEEE 30-bus testing systems where the estimation errors are compared for both the conventional method and extended SEFM method.

Sustainability of biofuel in developing countries: case study Thailand and Tanzania

The growth of energy demand together with the consequent increase of the cost of oil is great threats in developing countries economy. Alternative and sustainable energy such as biofuel seems to be a quick solution to this problem. The emerging industry is facing a lack of feedstock supplies, so it needs initiatives in crop cultivation technologies and competitive sourcing of appropriate feedstock which can alter the biofuel economics in developing countries. Some of biofuel production supply fall in food crops such as: cassava; maize; sorghum; etc., which is another critical need in developing countries. Since the biofuel production needs to be stable supply for the industry and also cost effective, a decision on which crop to put online with fuel production in developing countries while optimizing income is expressed in this paper. In this paper, several alternatives influenced by the geographical location of the country, economy and demand are analyzed and results are presented.

OPTIMAL PID TUNING FOR POWER SYSTEM STABILIZERS USING ADAPTIVE PARTICLE SWARM OPTIMIZATION TECHNIQUE

An application of the intelligent search technique to find optimal parameters of power system stabilizer (PSS) considering proportional‐integral‐derivative controller (PID) for a single‐machine infinite‐bus system is presented. Also, an efficient intelligent search technique, adaptive particle swarm optimization (APSO), is engaged to express usefulness of the intelligent search techniques in tuning of the PID—PSS parameters. Improve damping frequency of system is optimized by minimizing an objective function with adaptive particle swarm optimization. At the same operating point, the PID—PSS parameters are also tuned by the Ziegler‐Nichols method. The performance of proposed controller compared to the conventional Ziegler‐Nichols PID tuning controller. The results reveal superior effectiveness of the proposed APSO based PID controller.

Chlorophylls Contents in Echinocactus grusonii Extract

Currently, Golden Barrel cactus extract is formulated in dietary supplements, on account of its powerful weight loss profit and antioxidant activity. Golden Barrel cactus grusonii (Echinocactus grusonii), a Thai cultivar Golden Barrel cactus which is known as the golden barrel Golden Barrel cactus was therefore investigated for total chlorophylls with the aim of developing as a dietary supplement in future. The chlorophyll contents of 3 and 6 years Echinocactus grusonii extracts were evaluated by High Performance Liquid Chromatography with a Grace-Vydac 201TP54 reversed-phase polymeric C18 column. The results showed that chlorophyll a and chlorophyll b are the main components of Echinocactus grusonii crude extracts also at higher level at age 3 years. It was found that the main chlorophylls contents are chlorophyll a and chlorophyll b at 2.94±0.55μg/ml and 1.63±0.14 μg/ml for 3 years Echinocactus grusonii. In addition, the amount of chlorophyll a and chlorophyll b show lower content at 1.11±0.25μg/ml and 0.67±0.01μg/ml for 6 years Echinocactus grusonii. In conclusion, Echinocactus grusonii age 3 years crude extracts showed total chlorophylls contents higher than at age 6 years. The phytochemical profile study of Echinocactus grusonii age 3 years and 6 years crude extracts are planned in the near future.