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Lin H.C.,National Chin - Yi University of Technology
IEEE Transactions on Industrial Electronics

The discrete Fourier transform (DFT) is still a widely used tool for analyzing and measuring both stationary and transient signals in power system harmonics. However, the misapplications of the DFT can lead to incorrect results caused by some problems such as an aliasing effect, spectral leakage, and picket-fence effect. A strategy of recursive group-harmonic power minimizing algorithm is developed for systemwide harmonic/interharmonic evaluation in power systems. The proposed algorithm can restore the dispersing spectral leakage energy caused by the DFT and regain its harmonic/interharmonic magnitude and respective frequency. Every iteration loop for harmonic/interharmonic evaluation can guarantee to be convergent using the proposed group-harmonic bin power algorithm. Consequently, not only high precision in integer harmonic measurement can be retained but also the interharmonics can be accurately identified, particularly under system frequency drift. The numerical example is presented to verify the proposed algorithm in terms of robust, fast, and precise performance. © 2011 IEEE. Source

Chen R.-M.,National Chin - Yi University of Technology
Expert Systems with Applications

The studied resource-constrained project scheduling problem (RCPSP) is a classical well-known problem which involves resource, precedence, and temporal constraints and has been applied to many applications. However, the RCPSP is confirmed to be an NP-hard combinatorial problem. Restated, it is hard to be solved in a reasonable time. Therefore, there are many metaheuristics-based schemes for finding near optima of RCPSP were proposed. The particle swarm optimization (PSO) is one of the metaheuristics, and has been verified being an efficient nature-inspired algorithm for many optimization problems. For enhancing the PSO efficiency in solving RCPSP, an effective scheme is suggested. The justification technique is combined with PSO as the proposed justification particle swarm optimization (JPSO), which includes other designed mechanisms. The justification technique adjusts the start time of each activity of the yielded schedule to further shorten the makespan. Moreover, schedules are generated by both forward scheduling particle swarm and backward scheduling particle swarm in this work. Additionally, a mapping scheme and a modified communication mechanism among particles with a designed gbest ratio (GR) are also proposed to further improve the efficiency of the proposed JPSO. Simulation results demonstrate that the proposed JPSO provides an effective and efficient approach for solving RCPSP. © 2010 Elsevier Ltd. All rights reserved. Source

He Y.J.,National Chin - Yi University of Technology
Optics Express

As compared to the well-known traditional couple-mode theory, in this study, we proposed a visual, graphical, and simple numerical simulation method for long-period fiber-grating surface-plasmon-resonance (LPG-SPR) sensors. This method combines the finite element method and the eigenmode expansion method. The finite element method was used to solve for the guided modes in fiber structures, including the surface plasmon wave. The eigenmode expansion method was used to calculate the power transfer phenomenon of the guided modes in the fiber structure. This study provides a detailed explanation of the key reasons why the periodic structure of long-period fiber-grating (LPG) can achieve significantly superior results for our method compared to those obtained using other numerical methods, such as the finite-difference time-domain and beam propagation methods. All existing numerical simulation methods focus on large-sized periodic components; only the method established in this study has 3D design and analysis capabilities. In addition, unlike the offset phenomenon of the design wavelength λD and the maximum transmission wavelength λmax of the traditional coupled-mode theory, the method established in this study has rapid scanning LPG period capabilities. Therefore, during the initial component design process, only the operating wavelength must be set to ensure that the maximum transmission wavelength of the final product is accurate to the original setup, for example, λ = 1550 nm. We verified that the LPG-SPR sensor designed in this study provides a resolution of ~-45 dB and a sensitivity of ~27000 nm/RIU (refractive index unit). The objective of this study was to use the combination of these two numerical simulation methods in conjunction with a rigorous, simple, and complete design process to provide a graphical and simplistic simulation technique that reduces the learning time and professional threshold required for research and applications of LPG-SPR sensors. © 2013 Optical Society of America. Source

He Y.J.,National Chin - Yi University of Technology
Optics Express

In this study, a novel D-shaped localized surface plasmon resonance (LSPR) fiber sensor was introduced. The construction of this sensor involved etching of a single-mode fiber on the cladding layer and core layer, followed by plating using nano-metal strips. The design and calculations of the entire sensor were based on a numerical simulation method combining the finite element method (FEM) and the eigenmode expansion method (EEM). By using graphical representations of the algorithm results, the excitation of the LSPR was clearly observed. The finished D-shaped LSPR fiber sensor possesses several excellent properties, including a short length (2494.4301 μm), high resolution (approximately 35 dB), and high sensitivity (approximately 20183.333 nm/RIU). In addition, compared with LPG-SPR fiber sensor, the framework provides three advantages, namely, a fabrication process that is compatible with semiconductor fabrication, as well as the low-temperature cross-talk and high-temperature stability of surface grating. © 2013 Optical Society of America. Source

Chen H.-C.,National Chin - Yi University of Technology
Applied Energy

The aim of this work is to present an optimization methodology for the installation capacity of a stand-alone hybrid generation system, taking into consideration the cost and reliability. Firstly, on the basis of derived steady state models of a wind generator (WG), a photovoltaic array (PV), a battery and an inverter, the hybrid generation system is modeled for the purpose of capacity optimization. Secondly, the power system is analyzed for determining both the system structure and the operation control strategy. Thirdly, according to hourly weather database of wind speed, temperature and solar irradiation, annual power generation capacity is estimated for the system match design in order that an annual power load demand can be met. The capacity determination of a hybrid generation system becomes complicated as a result of the uncertainty in the renewable energy together with load demand and the nonlinearity of system components. Aimed at the power system reliability and the cost minimization, the capacity of a hybrid generation system is optimized by application of an adaptive genetic algorithm (AGA) to individual power generation units. A total cost investigation is made under various conditions, such as wind generator power curves, battery discharge depth and the loss of load probability (LOLP). At the end of this work, the capacity of a hybrid generation system is optimized at two installation sites, namely the offshore Orchid Island and Wuchi in Taiwan. The optimization scheme is validated to optimize power capacities of a photovoltaic array, a battery and a wind turbine generator with a relative computational simplicity. © 2012 Elsevier Ltd. Source

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