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This study incorporated the social spider algorithm (SSA), which simulates the preying behaviors of a group of spiders, to explore energy-efficient train operations. In this SSA, the magnitude of the vibration signal transmitted by the prey on a simulated spider web was used to determine the location with the most abundant food, which was equivalent to the optimal solution for train acceleration. In addition, a random movement model was implemented in the SSA to facilitate its capability for both local and global search and thereby increase its probability in identifying the optimal solution. A railroad route in Taiwan was simulated to verify the feasibility of this approach; the simulated data were then compared with the measured data from the actual test. According to the measured data, the SSA can formulate feasible railroad energy conservation plans and can assist locomotive engineers in planning their train operations. The results of the SSA were also compared to those of the teaching–learning-based optimization, to validate the superiority of the SSA.

With increasing dependence on precision electronic equipment, self-protection is becoming essential. The protection circuits commonly used before were fuses and circuit breakers which, however, they are not enough for the current need of high-speed protection circuits and automated engineering logic. In this paper, we develop a new ultrahigh-speed protection circuit, which is over exceeded 20 times faster than traditional circuits and has the ability to self-recover when any failure occurs. With the new circuit developed, it is not necessary to do manual restart and will meet the future needs of protection for electronic precision equipment. This design provides greater convenience and reliability for the unmanned equipment for the future.

The purpose of this study was to investigate the effect of using brainwave cloud classroom program on the brainwave’s changes in elderly. The sample of this study were fourteen participants, which were four men and ten women, aged 61-84 years old. All participants were measured their brainwaves prior to the brainwave cloud classroom program training. During the training, should any participant could not proceed to the next session, he/she was measured their brainwaves again. They were allowed to break for fifteen to thirty minutes. Then, the second training was done and that participants were measured their brainwaves again. The result showed that delta, theta, alpha, and beta brainwaves were gradually decreased with no statistically significant while gamma brainwave did not change.

This paper presents a novel 3-kW three-bladed vertical-axis micro-hydro turbine (VAMHT) system. The experimental results reveal that using this type of turbine in water is distinct from using it in wind. The micro-hydro turbine system uses a three-phase permanent magnet symmetric generator that transforms mechanical energy into electrical energy. The output voltage and frequency of the generator depend on water flow speed, and voltage steady equipment is used to maintain the maximum output power of the DC bus. According to the maximum power point tracking of the micro-hydro turbine system, the condition monitoring of the novel micro-hydro turbine requires no water flow meter. Furthermore, the construction and installation of the new micro-hydro turbine is simple, economical, and stable. This system combines a micro-hydro generator and electrical state-monitoring system, which can measure the speed, output power, DC-bus voltage, and all electrical characteristics of the micro-hydro turbine system. The results of comparing turbine between wind and water show that the speed ranges of water flow is narrower than that of wind, and the status transformation from cut-into stable power generation is short.

Nowadays, the research of the battery with higher energy density is increasing. Due to the higher energy density of battery, more and more machines are powered by batteries, such as electric vehicle, electric stacker trucks, and electric boat. Due to increasing energy density of batteries, the measurement of state of charge is facing a challenge. Because the voltage of lithium iron battery is quite stable, and its voltage is directly mapped into the state of charge, and the nonlinearity of the relationship between battery voltage and capacity make the measurement error is higher.

This study presents a multivariable linear generator which can convert wave energy directly into electrical energy. Based on the varying induction segment length over time, this study established an operational simulation of the multivariable linear generator while simultaneously constructing a multivariable generator device that considers the relationship between the number of vertical movements, the change in induction coils, the magnetic flux density, and other coefficients. Using finite element analysis, this study then analyzed the magnetic flux distribution for a single-stem linear generator and optimized the wiring. This method can be used to determine the wiring direction and coil thickness. The attraction between the magnet and the iron core is used to overcome the alternating magnetic fields, and linear motion with less stress is used to generate power. The generator developed in this study can generate 21.21 W power in 0.36 square meters area. We built a low cost, simple structure and multi-purpose human kinetic energy linear generator first for demonstration.

This study proposes a novel method using Jiles-Atherton model parameters to identify small fault current results from winding turn-to-turn short circuit in power transformer inrush current. The waveform symmetry and hysteresis curve shapes of inrush current with fault current are different from inrush current without fault current; that means the magnetic parameters of transformer cores and windings are influenced. Moreover, cycle leakage inductance and cycle winding resistance also can be used to distinguish inrush current and internal fault current due to changes of permeability and the winding current density caused by transformer core or winding state changes. Jiles-Atherton parameters per cycle, leakage inductance per cycle, and the winding resistance per cycle are estimated from the exciting inrush current per cycle under no-load conditions using the differential evolution algorithm. This study uses two types of parameters: the first is the correlation coefficient of Jiles-Atherton parameters of a transformer under no-load exciting condition. The second type is the variation trend of the cycle leakage inductance and the cycle winding resistance. The study uses cross validation of the two methods to distinguish whether inrush current contains small fault current. The experiment has verified the feasibility and accuracy of the proposed methods in this study.

The Bed Pressure Fluctuation Analysis (PFA) and dual electrical resistivity probe methods were used to investigate the hydrodynamic properties in a bioreactor. It was found that the dominant frequency and side frequency signals were not obvious from Hydraulic Retention Time (HRT) 4 to 0.5 h on the power spectrum diagram when using condensed molasses fermentation soluble (CMS) as the substrate in a biohydrogen production reactor. The start-up testing and online monitoring of the bed pressure fluctuation in a pilot system with HRT 12 h was also investigated. The pressure fluctuation analysis method established a hydrodynamic behavior diagram that was effective in determining flow regime of biogas in large-scale bioreactors. Finally, the study found that a mathematical model built using MATLAB to calculate and simulate the dynamic behavior of bubbles in a biological hydrogen production reactor satisfactorily. The bubble rise velocity and bubble size increased from 0.7 to 1.5 cm/s and 0.2 to 1.9 × 10 −6 cm respectively when the biogas production rate was increased from 30 to 70 mL/min in the biohydrogen production reactor.

This study proposes a fuzzy control bio-hydrogen internal combustion engine (ICE) generating system. The ICE technology is composed of thermodynamics, mechanical engineering, hydrodynamics, and electrical engineering. Bio-hydrogen can provide clean and efficient power instead of conventional fuels applied in an ICE. The two critical cores of hydrogen ICE generator are ignition time control which can precisely ignite air–fuel mixtures to make generator output stable power and air–fuel ratio control which can adjust output power to satisfy load demand. Fuzzy logic can provide precise control and response fast within various air–fuel ratios. The study establishes a fuzzy control system with an output generator and an ICE with solenoid valve that controls bio-hydrogen injection. The experimental system successfully output stable power and carried out parameters of bio-hydrogen flow rate, air–fuel ratio, injection pressure, and ignition timing. Parameters and experimental data are analyzed in the study and can be references for future development of the bio-hydrogen internal combustion engine generating system.

By comparing the differential evolution and genetic algorithms, this study attempts to optimize estimation of a biohydrogen real time power generating system in which circuit parameters fluctuate with operating temperature and current density. Based on uses of the differential evolution algorithm method, optimal estimation of the circuit parameters is achieved by data from a V – I characteristic experiment on the proposed biohydrogen real time power generating system. The circuit feature is then solved by formulating the estimated circuit parameters based on Kirchhoff’s law to elucidate its feature of the biohydrogen real time power generating system and results show that DE is faster than GA and more accurate. Next, the estimated V – I characteristics are compared with measurement results to demonstrate the feasibility of the proposed method.

The number of energy-consuming products is increasing. The use of renewable energy has already become the global goal to solve the global energy shortage. The development of the fuel cell is an important subject. This study plots the V–I characteristic curve of fuel cells using LabView. The experimental result demonstrates that the efficiency with which a fuel cell generates electricity when controlled by a Fuzzy controller is 37% – which significantly exceeds that obtained using a PID controller, 14.67%. Hence, much less bio-hydrogen is wasted, so the cost of generating electricity using the fuel cell is lower. Moreover, the Fuzzy controller need not be used for a long time as a PID controller to estimate and test variables. This research will contribute to the development of the bio-hydrogen fuel cell generators.

Long-term voltage records of coupling capacitor voltage transformers (CCVTs) indicate that CCVT voltage is occasionally distorted under normal operating conditions. Serious voltage distortion in CCVTs can cause the protection relay to trigger a circuit breaker (CB). This work analyzes the reasons accounting for voltage distortion of CCVTs and the impact of voltage distortion due to deterioration of gap insulation in CCVTs. In this work, the CCVT parameters are measured by using an LCR meter in a power laboratory. The electromagnetic transients program/alternative transients program software is used to establish a CCVT model. Finally, the simulating results are compared with the test records to confirm that voltage distortion is caused by an instantaneous short-circuit fault in the CCVT gap. Additionally, simulation analysis confirms that a permanent short-circuit fault at the gap burns the damping resistor in the CCVT, and the protection relay warns of a burden voltage drop at the secondary side of the potential transformer.

This study performs optimal estimation of circuit parameters for a biohydrogen real-time power generating system by using a penalty-function genetic algorithm (GA). Circuit parameters of this system change with operating temperature and current density; some circuit parameters are nonlinear. To elucidate the circuit characteristics of the whole system, this study uses penalty-function GA to optimally estimate circuit parameters using data from a V – I characteristic experiment on novel biohydrogen real-time power generating system. This study then solves the circuit characteristic by the estimated circuit parameters formulated utilizing Kirchhoff's law. Then, the estimated V – I characteristic is then compared with actual measurements to verify the feasibility of this novel approach. In the same manner, the capacitor parameter of the biohydrogen real-time power generating system can be estimated to identify the alternating current (AC) equivalent circuit for this system.

The subject of this paper is to construct a current- transformer (CT) model based on the Jiles-Atherton (J-A) theory of ferromagnetic hysteresis using transient analysis of control systems (TACS) functions within the electromagnetic transients program (EMTP) in a closed-loop manner. The J-A theory of ferromagnetic hysteresis is presented by the nonlinear first-order ordinary differential equations and inclusive of five parameters that can be found by measurements of hysteresis characteristic. We can use TACS functions within EMTP to describe the J-A theory of ferromagnetic hysteresis. The powerful advantage of this way is the interaction between the electrical network and TACS in EMTP. Compared with the CT model based on the type 96 nonlinear hysteresis inductor, the simulated result of the CT model based on the J-A theory of ferromagnetic hysteresis is almost the same in steady-state situations, but apparently different in a fault transient situation. The analysis and simulation of the actual measured fault profiles in the Taiwan power system is an example of the validation of this proposed model. Therefore, this proposed CT model based on the J-A theory of ferromagnetic hysteresis has the analysis capability of the transient response. The flexibility of TACS makes the simulation of any other situation easier and is another advantage.

This study aims to establish equations for energy consumptions of Taiwan Railways Administration (TRA) trains in operation considering the variations of slope to determine the traction energy cost (TEC). Where railway transportation has been one of the important means of transport for mankind, since TRA became electrified the parameters for train operations have been able to be accurately recorded. The equations for overall energy consumption and resistance parameters are completed for the overall energy consumption of TRA trains and resistance to them to simulate the operation of the whole train model. The inputs of different conditions of trains and track sections are then analyzed for energy use, as the energy use by train travel is obvious. That by the behavior of energy use, can be divided in three conditions for analysis which is acceleration, coasting and deceleration. In the analysis of the energy in the journey, the variation of its consumption is subject to multiple factors because of the difference in operation model and the variation in the track slope data. In view of decreasing unnecessary energy consumption, the equations for train energy consumption and the track parameters are substituted in the teaching-learning-based optimization (TLBO) technique, which can compute the optimal results fast. The optimal results being incorporated in the trains can help reduce unnecessary energy consumption and errors by human operations and arrive at the destination on schedule. By the equations for energy consumption, train parameters, and TLBO, our study proved to be able to reduce energy use as well as ensure of Top Transport Time Expenditure (TTE) of the trains.

In a transformer, the harmonic model is essential for the filter design and analysis of harmonic power flow. Among all of the harmonic analyses of nonlinear devices, the core nonlinearity caused by the transformer hysteresis has received the most interest. Although many harmonic models have been proposed to interpret the nonlinearity of the transformer core, most of them require complex calculations. In this study, we derive the mathematical formulas of the exciting current for a single-phase transformer by the describing function methods. The mathematical expression allows us to obtain the Fourier series for the exciting current; and, then, it provides the various order harmonic magnitudes and phase angles of the exciting current. This work also presents a mathematical model characterized by simple calculation and with high precision for the harmonics of exciting current. The transformer is under no load condition. Actual measuring verifies the effectiveness of the proposed model.

Production simulation is effective in evaluating the production cost, fuel demand and reliability of generation systems. Among the most important methodologies that presently exist for production simulation, one numerical and three analytical methods (including the Mixture of Normal Approximation, MONA) are reviewed. In this paper, reasons for the high computing efficiency of the analytical methods and the relatively high simulation accuracy of the MONA method are identified. In this paper, the MONA method's load categorization is improved. The MONA with an improved load categorization has been compared numerically with the four aforementioned existing methods, including the conventional MONA, by testing on two benchmark test systems. The results demonstrate the characteristics of the four existing methods and the effectiveness of the proposed load categorization technique.

A computer algorithm which combines several variance reduction techniques to enhance the precision of Monte Carlo production simulation is designed. The techniques included are stratified and antithetic samplings and linear regression estimation. For stratified sampling, a mathematical rule which can always lead to a near-optimum stratification is presented. The variance reduction by modelling generating units' outage according to their uptime/downtime distribution in comparison with modeling by forced outage rate is investigated. Numerical test results achieved by applying the algorithm to cost and environment evaluations in an actual Taiwan power system are examined. >

A capacitively coupled VHF H2 plasma (60 MHz) was produced at high pressures, and plasma parameters were examined as a function of pressure and power at different discharge gaps (10, 15, and 20 mm). Here, a balanced power feeding method was adopted to avoid anomalous discharges. It was found that the electron density peaked at a certain pressure. As the discharge gap decreased, the peak pressure increased. The electron temperatures at the discharge gaps of 10 and 20 mm were approximately 8 and 3 eV at high pressures, respectively. In addition, we found that the sheath potential corresponding to the ion bombardment energy with the discharge gap of 10 mm was lower than the theoretical value calculated on the basis of the sheath theory, suggesting the existence of negative ions. Estimation of negative ion concentration was attempted on the basis of the sheath theory taking into consideration negative ions.

This thesis applies a self-reunion multiple regression (SRMR) model in short-term load forecasting (STLF) and obtains very accurate and steadfast results. This thesis first uses cluster analysis to categorize historical data. Data with similar features will be put in one category. After that, select one group of multiple regression variables in different categories, which serves as the basis for the load forecasting. Then, determine each selected multiple regression variables' regression function for the predicted load by taking the regression function as the base for the forecasting model and using the least-square error. Finally, with the linear programming, find the reunion coefficient corresponding to each regression function. The SRMR model obtained through the fore-going steps is tested by the actual Taiwan load data. Results prove that the average forecast absolute error sought by the model is about 1%, better than the error by the traditional methods

In this paper the transmission line equation which describes the transient voltage and current distributions of a lightning stroke is employed. The finite element method is used to derive the element equations and one-dimensional linear elements are used to discretize the field region. The implicit Newmark time integration technique is used to convert the resulting second-order ordinary differential equations into a set of recurrence equations which are then solved at each time step. A numerical example is included and discussed.

The western Taiwan railway consists mainly of a mountain route and ocean route. Taiwan Railway Administration (TRA) has conducted a series of experiments on the ocean route to identify the possible causes of unknown events which frequently cause trolley contact wires meltdown. The tests conducted include the short circuit fault test within the power supply zone of the Ho Long Substation (Zhu Nan to Tong Xiao) that had the highest probability for the meltdown events. Those test results based on the actual measured maximum short circuit current provide a valuable reference for TRA when comparing against the said events. Le Blanc transformer is the main transformer of the Taiwan railway electrification system. The Le Blanc transformer mainly transforms the Taiwan Power Company (TPC) generated three phase alternating power supply system (69 kV, 60 Hz) into two single phase alternating power distribution systems (M phase and T phase) (26 kV, 60 Hz) needed for the trolley traction. As a unique winding connection transformer, the conventional software for fault analysis will not be able to simulate its internal current and phase difference between each phase currents. Therefore, besides extracts of the short circuit test results, this work presents an EMTP model based on Taiwan Railway Substation equivalent circuit model with Le Blanc transformer. The proposed circuit model can simulate the same short circuit test to verify the actual fault current and accuracy of the equivalent circuit model. Moreover, the maximum short circuit current is further evaluated with reference to the proposed equivalent circuit.

The harmonic current of the Le Blanc transformer of the Taiwan railway system is measured to determine how it reduces the power supply capacity to the trolley (nonlinear load). Improvements to the harmonic current in point-of-common-coupling (PCC) after adding the double-tuned filter to the load side, are also described.

Unusual residual time of image sticking under high-voltage electrostatic discharge (ESD) stress on liquid crystal (LC) cells has been observed. It was found that nanoscaled conductive particles doped in LC cells can significantly reduce the residual time of image sticking and the breakdown voltage of the LC cells. This finding can help to protect the doped cells from the attacks of ESD and thus to improve their displaying performance and reliability. In this study, nanoscaled tin-doped indium oxide (ITO) powders were uniformly mixed with high-resistance LC to form a suspension solution. In order to investigate other effects of ITO particles on the LC at high and low voltages, optical and electrical characteristics were compared for the doped cells and those samples without intentional doping. According to the measurement results, it is interesting to find that, except the breakdown characteristic, no other properties in the doped samples were changed with respect to the displaying functions under normal operational voltage.

In this paper, a statistical methodology that can be used for the optimization of the Insulator Gate Bipolar Transistor (IGBT) devices is proposed. This is achieved by integrating the response surface method (RSM) with cluster analysis, weighted composite method and genetic algorithm (GA). The device characteristic of IGBT was simulated based upon the fabrication simulator, ATHENA, and the device simulator, ATLAS. This methodology, yielded another way to investigate the IGBT device and to make a decision in the tradeoff between the breakdown voltage and the on-resistance. In this methodology, we also show how to use cluster analysis to determine the dominant factors that are not visible in the screening of all experiments.

The western Taiwan railway transportation system consists mainly of a mountain route and ocean route. The Taiwan Railway Administration (TRA) has conducted a series of experiments on the ocean route in recent years to identify the possible causes of unknown events which cause the trolley contact wires to melt down frequently. The conducted tests include the short circuit fault test within the power supply zone of the Ho Long substation (Zhu Nan to Tong Xiao) that had the highest probability for the melt down events. Those test results based on the actual measured maximum short circuit current provide a valuable reference for TRA when comparing against the said events. The Le Blanc transformer is the main transformer of the Taiwan railway electrification system. The Le Blanc transformer mainly transforms the Taiwan Power Company (TPC) generated three phase alternating power supply system (69 kV, 60 Hz) into a two single-phase alternating power distribution system (M phase and T phase) (26 kV, 60 Hz) needed for the trolley traction. As a unique winding connection transformer, the conventional software for fault analysis will not be able to simulate its internal current and phase difference between each phase currents. Therefore, besides extracts of the short circuit test results, this work presents a EMTP model based on a Taiwan Railway substation equivalent circuit model with the Le Blanc transformer. The proposed circuit model can simulate the same short circuit test to verify the actual fault current and accuracy of the equivalent circuit model. Moreover, the maximum short circuit current is further evaluated with reference to the proposed equivalent circuit. Preliminary inspection of trolley contact wire reveals the possible causes of melt down events based on the simulation results.