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The concept of the smart city has been created in response to the increasing numbers of people living in cities. Just as the development of technology has evolved rapidly, smart life has also emerged. The goal of the smart city is one day to enable all affairs of daily life to be completed with the single touch of a finger through cutting-edge technology. New and innovative information must be applied effectively to the industry. With the industrial revolution, propelled by the Internet of Things (IoT), big data and the cloud platform have birthed the “smart city,” integrating the IoT and the cloud through mobile devices and applying technology to fields like logistics, finance, healthcare, recreation, surveillance, and traffic transportation, thus providing people with greater well-being and convenience. Following the era of the big data knowledge economy, the IoT has become an important pillar of national economic development. The IoT is expected to provide substantial support for continued and sustainable development of the smart city. Therefore, effective use of the IoT has become an important topic in smart city development. The purpose of this paper is to build a conceptual framework of service innovation, relying on the smart city case of Taiwan. Based on a literature review, in-depth interviews, and case interviews, the proposed conceptual framework of IoT is rooted in the market, policy, and technical aspects. It incorporates eight steps: composition of the project team, service idea generation, service idea screening, development concept selection, design and development, service testing, commercialization, and service quality, to generate new service value and thereby create customer satisfaction. In fact, the IoT is designed to support the smart city vision; thus, this paper describes the various innovation modes of the smart city. Furthermore, the paper presents and discusses the technical solutions and best-practice guidelines adopted in the Taiwan Smart City project. Finally, it discusses the meaning and future research direction of the smart city through the use of the IoT. With wave after wave of digital development civilizing the city's evolution and with the phenomenon of Internet access through mobile phones for each person, the smart city of human factors is clearly coming. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing interest in open government data (OGD) around the world. The governments of various countries have encouraged firms to adopt OGD to develop innovative products and services to bring about social and economic benefits. This paper examines the factors influencing the adoption of OGD among firms in Taiwan to fill a gap that prior studies do not adequately address. Based on the sociotechnical perspective, we developed a research model that integrates the following factors that are central to adoption decisions of firms: top management support, government support, competitive pressure, perceived benefits, and perceived barriers. We examined this model through survey data from firms with experience in OGD adoption in Taiwan. The results show a significant positive relationship among top management support, competitive pressure, and the adoption of OGD by firms. This paper serves as a first attempt to contribute to advancing knowledge on OGD adoption at the firm level via empirically testing a research model that integrates factors within social and technical systems. This paper has significant implications for practitioners of enterprise information management and creates a valuable reference for other countries in the early stages of OGD initiatives. [ABSTRACT FROM AUTHOR]

The displacement of synchronous generators by converter interfaced energy renewable resource essentially reduces the system inertia, which can trigger under-frequency load shedding relay. To support the frequency containment, virtual inertia control (VIC) and fast frequency control (FFC) based on energy storage system (ESS) have been developed. Most of the existing VIC did not take into account the power constraints of the ESS. Although some of the FFC methods account for the ESS constraints, they ignore the intermediate steady-state (ISS) operating point of the primary frequency response (PFR). To counteract these problems, a model predictive control (MPC) based FFC, which considers the power limitations of the ESS, the frequency deviation constraint, and the ISS frequency tracking capability, is proposed in this paper. The proposed MPC only requires few local measurements, and the system parameters including inertia constants, onset time of inertia response and the ISS time of the PFR can be accurately estimated. To achieve the optimal control action and reduce computational burden, quadratic programming (QP) is incorporated in the proposed MPC. The proposed MPC is tested on a real Taiwan power system. The fast response and robustness of the proposed MPC has been justified by comparing with the state-of-the-art method. [ABSTRACT FROM AUTHOR]

The annual output value of Taiwan’s wafer foundry and IC packaging test ranks first worldwide. The electronics industry has a complete industrial ecological chain in the supply chain system of global information and communication technology. In order to increase market competitiveness and increase the operational flexibility, manufacturing process outsourcing has become a trend in the business model of the electronics industry. The quality of the outsourcing affects the quality and function of the final product, the outsourcer selection is crucial to ensure the quality of the final product. This article takes the wire bonding process as an example, and proposes a fuzzy selection model of quality-based IC packaging process outsourcers. Then, this article selects the six standard deviation indicator that can fully reflect the process yield and quality level as the evaluation tool. Since the indicator contains unknown parameter, in order to improve the accuracy of estimation and overcome the uncertainty of measurement data, this paper applies mathematical programming to derive the confidence interval of six sigma quality index, and proposes a confidence-interval-based fuzzy testing meth as a green outsourcer selection tool to reduce the risk of misjudgment due to sampling errors and improve the accuracy of the selection. [ABSTRACT FROM AUTHOR]

A fast retransmit, which reduces the sender’s waiting time before retransmitting a lost segment, is applied to guarantee data integrity with no data loss in transmission. Based on fast retransmit, many application protocols have been enhanced and evolved to ensure quality of service and reduce data transmission time. One of application protocols is the multipath transmission control protocol which is catholically applied in modern computer networks. Communication lines used in this kind of network have different states, namely, failure, partial failure, and maintenance. Therefore, a computer network with a fast retransmit can be classified as stochastic and is called a stochastic-flow computer network with a fast retransmit (SCNFR). This paper assesses the system reliability of SCNFR for the successful transmission of demand d through ${k}$ (${k} \,\, >1$) separate minimal paths (${k}$ SMiP) under the latency. An algorithm is proposed to find all minimal capacity vectors (MCVs) that satisfy the demand and latency. Then, the system reliability is computed based on all MCVs. We adopt two practical cases of the pan-European research and education network and the Taiwan academic network to explore the effectiveness of the algorithm. The results show that the system reliability can be classified as decision reference while the manager decides the better ${k}$ SMiP with higher system reliability. [ABSTRACT FROM AUTHOR]

Submarine cables are indispensable for offshore wind farms (OWFs) connected to a power grid. The submarine cable can cause certain degrees of impact on the system performance due to its different lengths, characteristics, electrical parameters, etc. This paper employs the power-system simulation software of Power System Simulator for Engineering (PSS/E) for modeling a future-scheduled OWF, i.e., a large-scale doubly-fed induction generator-based OWF of 200 MW, connected to Jang-Bin distribution substation of Taiwan Power System through five feeders, five circuit breakers, two step-up power transformers, a commercial submarine cable, and an underground cable. This paper simulates and compares the electrical quantities of the studied OWF with different operating capacities under various lengths of three types of commercial submarine cable. The transient surge peak voltages at the common bus of the OWF and the bus of Jang-Bin distribution substation subject to the switching of one of the five circuit breakers of the studied OWF under different lengths of the three types of commercial submarine cable are also compared using the power-system simulation software of ATPDraw in Alternative Transients Program (ATP) version of Electromagnetic Transients Program (EMTP). [ABSTRACT FROM AUTHOR]

In a power system, the transmission network is the backbone of electricity delivery from power plants to load centers; hence, it becomes a critical issue for electrical engineers to shorten the service restoration time after a fault occurrence on the transmission line. This application paper integrates the two- and three-terminal hybrid transmission line fault location algorithms based on synchronized phasor measurements into the proposed cloud-computing-based fault location system to inspect the feasibility and practicality of our algorithms for the real transmission-line incidents. The computing results are performed via Google Map for authorized personal computers and the application for intelligent mobile devices is developed to assist engineers in acquiring the fault-event information immediately as well as in figuring out the fault position intuitively and quickly due to its visualization and navigation. Last but not the least, the suggested fault location system has already been applied to the practical 345- and 161-kV transmission networks of Taiwan Power Company for achieving the combination of theory and practice. Up to the present, the proposed system still yields excellent performance verified by realistic fault data. [ABSTRACT FROM AUTHOR]

An optimal planning model of the sectional switch and tie line for the distribution network is proposed considering the tradeoff between the system reliability and economy. First, the fault incidence matrices are established for the distribution network, and the explicit analytical expression of the system reliability index is realized by the algebraic operation of the fault incidence matrices and fault parameter vectors. Then, the 0–1 integer quadratically constrained optimization model is established for the sectional switch configuration considering the capacity constraint of the tie line. Finally, the sectional switches and tie lines are optimized jointly to ensure the economic investment and maximize the system reliability. The distribution network in Taiwan Power Company is used to verify the applicability of the proposed optimization method. Compared with the intelligent optimization algorithm, the mathematical programming method in this paper can always find the global optimal switch configuration quickly. In addition, the influence of the tie line capacity constraints on the sectional switch configuration is also considered, which can provide practical reference for the power network planners in the optimization design of the distribution network. [ABSTRACT FROM AUTHOR]

In the semiconductor industry, the testing section has always played an important role. The testing section often requires engineers to judge the defect, which wastes a lot of time and cost. The accurate classification can provide useful information for engineers through neural networks. In this paper, we present a method for wafer map data augmentation and defect classification. Data augmentation is based on CNN encoder-decoder and the classification is based on depthwise separable convolutions. There are two datasets used, one is open dataset WM-811K and the other is built with a Taiwan company. We train two models with mobilenetV1 and V2 for the different datasets. The light-weight deep convolution can reduce model parameters and calculations, which is very efficient for the testing house with large production volumes. On two different data sets, our proposed method can reduce the number of parameters by 30% and 95%, and reduce the amount of calculation by 75% and 25%, respectively. The test accuracy of the first dataset is 93.95%. The second dataset test accuracy is 87.04%. After the data augmentation, accuracy is increased to 97.01% and 95.09%, respectively. [ABSTRACT FROM AUTHOR]

In urban environments, Global Positioning System (GPS) signals are often reflected or blocked by buildings causing multipath effects and Non-Line-Of-Sight (NLOS) reception. These effects degrade GPS positioning performance. Although improved receiver and antenna design can reduce the multipath effect to some extent, NLOS elimination is limited due to sensor cost. Measurements based modelling methods have shown promise to reduce NLOS, while positioning accuracy is limited by the correct classification of the signal reception types. These limitations are addressed in this paper by developing an integrated algorithm using matching, Particle Swam Optimized Adaptive Neuro Fuzzy Inference System (PSO-ANFIS) and a spatial city model. The user's location is determined by matching the high accuracy signal reception type determined by PSO-ANFIS with satellite visibility of each candidate position determined by the ray-tracing and a 3D city model. The results from a field test in an urban area in Taiwan show that the PSO-ANFIS based algorithm achieves a classification accuracy of 96%, 88%, and 91% for LOS, multipath and NLOS signals, respectively, which is superior to the other classification algorithms. The final horizontal positioning accuracies in terms of the Root Mean Square Error (RMSE) are 3.20 m using a commercial receiver and 1.88 m using a geodetic receiver. The proposed algorithm has consistent improvements of 88% and 70% respectively compared to the traditional Weighted Least Square (WLS) based positioning method, and is the best compared to the other state-of-the art methods with the improvements ranging from 15% to 77% depending on the test conditions. [ABSTRACT FROM AUTHOR]

Earthquake early warning system uses high-speed computer network to transmit earthquake information to population center ahead of the arrival of destructive earthquake waves. This short (10 s of seconds) lead time will allow emergency responses such as turning off gas pipeline valves to be activated to mitigate potential disaster and casualties. However, the excessive false alarm rate of such a system imposes heavy cost in terms of loss of services, undue panics, and diminishing credibility of such a warning system. At the current, the decision algorithm to issue an early warning of the onset of an earthquake is often based on empirically chosen features and heuristically set thresholds and suffers from excessive false alarm rate. In this paper, we experimented with three advanced machine learning algorithms, namely, $K$ -nearest neighbor (KNN), classification tree, and support vector machine (SVM) and compared their performance against a traditional criterion-based method. Using the seismic data collected by an experimental strong motion detection network in Taiwan for these experiments, we observed that the machine learning algorithms exhibit higher detection accuracy with much reduced false alarm rate. [ABSTRACT FROM AUTHOR]

As the penetration of photovoltaic (PV) solar generation has increased, a significant number of residential and commercial solar PV systems have been installed without meters. The majority of these systems, however, are also not monitored by power system operators. Therefore, the uncertainty of the net load owing to this “invisible” solar power generation has raised additional challenges for power system operation. To reduce the impact of this, we propose a novel method to estimate the total solar power generation in a large region from a small representative subset. The proposed method is capable of capturing all relevant information that could assist in the identification of the representative subsets. Moreover, different optimization algorithms are utilized and evaluated to select the optimal number of clusters and representative subsets. As a case study, the power generation of 166 PV sites in Taiwan was collected and analyzed. The proposed method demonstrates a significant improvement in estimating aggregated power generation compared to other existing methods. [ABSTRACT FROM AUTHOR]

The progress of industrial development naturally leads to the demand for more electrical power. Unfortunately, due to the fear of the safety of nuclear power plants, many countries have relied on thermal power plants, which will cause more air pollutants during the process of coal burning. This phenomenon as well as increased vehicle emissions around us, have constituted the primary factors of serious air pollution. Inhaling too much particulate air pollution may lead to respiratory diseases and even death, especially PM $_{2.5}$ 2. 5 . By predicting the air pollutant concentration, people can take precautions to avoid overexposure to air pollutants. Consequently, accurate PM $_{2.5}$ 2. 5 prediction becomes more important. In this study, we propose a PM $_{2.5}$ 2. 5 prediction system, which utilizes the dataset from EdiGreen Airbox and Taiwan EPA. Autoencoder and Linear interpolation are adopted for solving the missing value problem. Spearman’s correlation coefficient is used to identify the most relevant features for PM $_{2.5}$ 2. 5 . Two prediction models (i.e., LSTM and LSTM based on K-means) are implemented which predict PM $_{2.5}$ 2. 5 value for each Airbox device. To assess the performance of the model prediction, the daily average error and the hourly average accuracy for the duration of a week are calculated. The experimental results show that LSTM based on K-means has the best performance among all methods. Therefore, LSTM based on K-means is chosen to provide real-time PM $_{2.5}$ 2. 5 prediction through the Linebot. [ABSTRACT FROM AUTHOR]

If an extreme contingency strikes the Kinmen Island power system in Taiwan, it is very likely to cause blackouts. Although an underfrequency protection scheme has been applied, some drawbacks of the protection scheme hinder the Kinmen power system from avoiding blackouts. In the past decade, several blackouts have occurred in the Kinmen power system. To avoid further possible blackouts, a special protection system (SPS) is summoned. This paper describes the design guidelines and deployment procedures of an SPS for the Kinmen power system. The design depends on the Kinmen power system characteristics, and the deployment hinges upon the supervisory control and data acquisition system. Exquisite software was also developed to testify the Kinmen system SPS. Operational records have demonstrated that the proposed SPS can indeed prevent blackouts from occurring in the Kinmen power system. The design, implementation, and operation of the SPS dealt with in this paper might foster further deployments of other SPSs. [ABSTRACT FROM AUTHOR]

In the semiconductor manufacturing industry the development of single index assessing the equipment health condition is urgent, and thus the dashboard can be used for monitoring thousands of equipment. This paper proposes a novel equipment health index (EHI) framework and a Hotelling T-squared index (HTI) to monitor equipment and support preventive maintenance in real time in the semiconductor manufacturing industry. The EHI framework consists of data preprocessing, statistical process control, analytic hierarchy process, and a comprehensive single index representing the health condition of equipment. It considers different types of the univariate control charts for each status variable identification (SVID), and aggregates the scores corresponding to the control charts throughout the hierarchical structure. The HTI considers the correlation among the selected SVIDs and builds a multivariate index by using Hotelling T-squared statistic. An empirical study of Taiwan’s leading semiconductor assembly manufacturer finds that both the EHI and the HTI supported monitoring thousands of pieces of equipment in real time. In practice, firms can rapidly troubleshoot the root causes of failures by the decomposition of EHI. [ABSTRACT FROM AUTHOR]

This paper presents the design, implementation, and field measurements of a prototype marine-current power generation system (MCPGS) for capturing energy from marine current. The studied prototype MCPGS employs the flowing marine-current energy near the Cross-Sea Bridge, Peng-Hu Island, Taiwan. The design of the prototype MCPGS has to meet the practical marine-current flowing conditions and the severe environmental conditions in the ocean of Peng-Hu Island. The designed MCPGS unit consists of a three-blade marine-current turbine, a gearbox, a three-phase permanent-magnet generator, and a power converter that is used for converting generated energy to be stored in the battery. Field measured results for the studied MCPGS under different practical marine-current speeds in Peng-Hu Island are performed and analyzed. [ABSTRACT FROM AUTHOR]

Fault detection and classification has been employed to enhance yield and product quality for smart semiconductor manufacturing. For early detection of abnormal events that cause defects, the status variables identification data collected by the sensors embedded in advanced machines can be analyzed to derive the actions for advanced process control and advanced equipment control. However, the validity and effectiveness of fault detection and classification technologies may highly depend on domain knowledge and experience of the process engineers who should redefine the monitoring rules quickly when new process excursion occurred especially when ramping up new technologies and products. Motivated by realistic needs, this study aims to propose a novel strategy to empower intelligent fault detection and classification that employed convolutional neural network to analyze the feature SVID data and determine the conditions of the wafers, while shorten the cycle time for self-learning from domain knowledge and redefining new monitoring rules for fault classification in real time. This approach is validated with an empirical study in a leading semiconductor manufacturing company in Taiwan. The results have demonstrated the practical viability of the developed solution. [ABSTRACT FROM AUTHOR]

Variations of the ionosphere can significantly disrupt synthetic aperture radar (SAR) acquisitions and interferometric measurements of ground deformation. In this paper, we show how the ionosphere can also strongly modify C-band interferograms despite its smaller influence at higher frequencies. Thus, ionospheric phase screens should not be neglected: their compensation improves the estimation of ground deformation maps. The split-spectrum method is able to estimate the dispersive ionospheric component of the interferometric phase; we describe the implementation of this method for the burst modes TOPS and ScanSAR to estimate and remove ionospheric phase screens. We present Sentinel-1 interferograms of the 2016 Taiwan earthquake and ALOS-2 interferograms of the 2015 Nepal earthquake, which show strong ionospheric phase gradients, and their corrected versions. Finally, to validate the results and better understand the origin of these ionospheric variations, we compare the estimated differential ionosphere with global Total Electron Content maps and local Global Positioning System measurements. [ABSTRACT FROM PUBLISHER]

Because of climate changes, natural disasters are becoming more serious. For instance, the intensity of typhoons has been increasing in recent years. Typhoons and other natural disasters have high-impact low-probability characteristics. Thus, procedures for preparing for natural disasters and increasing power system resilience are important issues. This article proposes an all-inclusive process for system operators to make decisions for enhancing power system resilience and economic value during a severe weather event. This process first considers the typhoon track, the fragility curve and the recovery time of transmission lines. After collecting these data, system simulations and a calculated resilience index are implemented according to cases with and without disaster prevention. Next, the probability threshold and calculated economic value index are obtained based on numerical weather prediction wind speeds and the cost-loss ratio. Finally, the two indexes are considered in combination to obtain the highest resilience with the greatest benefit. The proposed process helps system operators make decisions for appropriate preventive actions at the least cost. An actual Taiwan power system and a severe weather event are used as an example to demonstrate the proposed decision analysis. The simulation results indicate the feasibility of the proposed method, which can reduce potential risks caused by extreme weather events with the maximum economic benefits. [ABSTRACT FROM AUTHOR]

The R&D output and global commercialization of intellectual properties (IPs), especially patents filed in many countries, have increased dramatically over the past decade. The overwhelming growth in research and IP activities has led to a major challenge to understand and forecast technology development insights and trends. Evidence-based data analytics is essential for technology mining. The assessment of patent values is a critical aspect of technology mining, which remains a highly subjective task performed by domain experts. As businesses become globalized, subjectivity in underlying assessments of large volumes of patent documents leads to overpriced or undervalued IP sales or licensing that exposes stakeholders to legal and financial risks. Thus, the development of intelligent methods for patent valuation requires new research emphasis. This article applies a deep learning analytical method for automatic and intelligent patent value estimation. Principal component analysis (PCA) is used to identify significant patent value indicators from the given patent dataset. Then, deep neural networks (DNN) for value prediction are modeled and trained using the training set. A detailed case study of 6466 manufacturing Internet of Things (IoT) patents is analyzed to demonstrate the improved results of building PCA-preprocessed DNN models to perform patent valuations. Finally, selected higher value IoT patents owned by leading Taiwan assignees are identified and analyzed to verify the technological competitive intelligence. [ABSTRACT FROM AUTHOR]

The west coast and islands of Taiwan have abundant wind resource, which offers a great opportunity for large-scale offshore wind power generation. In Taiwan, the first stage of the offshore wind farms at the Jhang-Bin and Penghu areas has been planned. In particular, the Jhang-Bin wind farm will become the first and one of the largest wind farms in Taiwan. Therefore, its impacts on system operation and security have to be investigated and studied in advance. Following a general connection design discussion, this paper is consist of four major system impact analyses: load flow, fault current, voltage variation, and transient stability. Moreover, three types of typical wind turbines have been adopted in this paper in order to compare their performances on the wind farm integration system. From the simulation results, some significant conclusion and recommendations have been extracted, which would contribute to the first offshore wind farm development in Taiwan. [ABSTRACT FROM AUTHOR]

This paper presents the effects of installing variable current-limit reactors (CLRs) and adjusting load tap changers (LTCs) on the performance of a commercial wind farm in Taiwan using computer simulations. The companion paper (Part I) demonstrates the field-measured results, simulation model, and simulation results of the studied Jang-Bin wind farm with 23 2-MW doubly fed induction generator-type wind turbine generators connected to the utility system through a 23/161-kV 60-MVA step-up main transformer (MT) from six feeders. Six CLRs, which were originally designed to limit short-circuit currents under faulted conditions, are connected in series with the six feeders. The LTCs of the MT are used to adjust/regulate the secondary-side voltage at the 23-kV bus. Some simulated steady-state and transient results of the studied wind farm with variable values of the proposed CLRs and LTCs are analyzed and compared. [ABSTRACT FROM PUBLISHER]

Most catch up studies focus on “external” foreign sources of technological learning as a means of building up latecomer technological capability. By contrast, strategic management studies in advanced countries center on the “internal” sources of organizational learning and routines (including R&D) within a firm, aimed at developing and renewing its knowledge and its absorptive capacity. This paper draws from both groups of studies to examine how latecomer firms accumulate in-house knowledge bases and assimilate foreign knowledge to create strategic innovation capabilities. We propose a clear three-stage development framework to examine two leading firms, AU Optronics (AUO) and Chimei Innolux (CMI), in Taiwan's flat panel display industry. This paper shows the coevolution of the firms’ knowledge bases and external foreign sources of knowledge over time. We find that, with their increasing knowledge bases and strategic advancement over time, the firms are able to benefit from knowledge transfer; to build up their high-level innovative capabilities, and in the process to move from junior to senior status with foreign firms. These developments appear to allow leading firms to move “across” the technological frontier, contributing to a strengthening competitive position in the international market. [ABSTRACT FROM PUBLISHER]

Recently, Taiwanese Government has announced an ambitious energy policy: up to 20% of total power will be generated from renewable energy resources by 2025. Under such high-level penetration level of renewable energy resources, the typical net load curve will be definitely reshaped as the so-called duck curve. Operation modes of pumped hydro storage units in Taiwan power system will be totally changed. To tackle out this difficulty, the optimal scheduling of Taiwan power system is developed in this article for examining the coordination of highly penetrated renewable energy resources and pumped hydro storage plants under the required spinning reserve. The associated cost function and various constraints used in this optimal scheduling problem are described first. Physical characteristics of pumped hydro storage units in Taiwan will also be studied. By following the data format in the open source MATPOWER optimal scheduling tool, platform developments of this optimal scheduling program are reported. To validate the effectiveness of the proposed scheme, intensive simulations of both current scenarios and future scenarios are conducted. Simulation results indicate that existing pumped hydro storage units in Taiwan can indeed mitigate the impact of the duck-shaped net load curve in the generator scheduling of future Taiwan power system even under the worst scenario. [ABSTRACT FROM AUTHOR]

The severe insulation breakdown on one medium-voltage (MV) switchgear led to a complete blackout of Taipower's 3rd nuclear power plant on March 18th, 2001. This has been one of the most serious incidents during the past 30 years of Taipower's nuclear generation and while the cause of the event was a combination of design, maintenance, and equipment aging issue, it is apparent that repeated switching operation on the extra-high-voltage (EHV) side eventually caused this severe insulation breakdown on MV switchgear. Very-fast transient overvoltage (VFTO) is the phenomenon of transient overvoltage generated during switching operation characterized by a very short rise time of 4 to 100 ns. Prior research on this topic focused on VFTO's impact on the EHV side of the transformer and this paper presents the field measurement result together with long-duration multiple-restrike simulation for the VFTO transferred from the EHV side to the MV system through the power transformers. It is shown that this VFTO can be as high as 7 times the rated line-to-ground peak voltage and the maximum VFTO often occusr neither at the first nor at the last strike due to the superposition of restriking voltage on top of oscillation voltage created by prior strikes. [ABSTRACT FROM AUTHOR]

This paper presents both steady-state performance and dynamic simulations of a commercial wind farm (WF) in Taiwan through field measurement results and computer simulations. The companion paper in Part II discusses the dynamic and transient analyzed results of using current-limit reactors (CLRs) and load tap changers on power-quality improvement of the studied WF. With 23 2-MW DFIG-type wind turbine generators, this WF is connected to the 161-kV extra high-voltage substation of Taiwan Power System through a 23/161-kV 60-MVA step-up main transformer from six feeders with CLRs. Through comparing field measured results, this paper establishes a simulation model to simulate and analyze the steady-state and dynamic characteristics of the studied WF which is subject to disturbance conditions under different wind-speed conditions. [ABSTRACT FROM PUBLISHER]

This paper proposes a technique for frequency-partitioned spectrum estimation (FPSE), which is used in the National Taiwan University Wireless Health Advanced Monitoring Bio-Diagnosis System for electrocardiogram analysis. A process for analyzing the RR interval (which is a time series formed by the heat-beat duration that represents heart-rate variations) in conjunction with the fuzzy clustering technique is proposed for arrhythmia recognition. FPSE helps reduce data transmission errors and allows the computational load to be moved to a remote server; however, it suffers from waveform deterioration during reconstruction of the signal power spectrum. To compensate for this problem, this paper proposes a modified FPSE approach that imposes an additional boundary constraint to ensure that the estimated spectrum is smooth. The simulation results show that the proposed algorithm is more effective at recovering the original frequency information and achieves a globally asymptotic trend. The proposed arrhythmia recognition procedure was applied to the Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) database (developed by MIT and Boston's Beth Israel Deaconess Medical Center), which demonstrated that it is both very convenient and efficient. [ABSTRACT FROM AUTHOR]

For isolated power systems, an efficient and effective ancillary services market is one of the most important tools to ensure the system security and service quality. It is recognized that pumped storage units can play a unique role in the operation of isolated power systems. As part of the introduction of the ancillary services for Taiwan, a study was performed to identify the role and value of pumped storage units in the fast-response reserve (FRR). This paper analyzes the actual dispatching schedules of pumped storage units in the Taiwan Power System (TPS) to provide FRR when system was operated under seriously insufficient conditions for the year 2004. The results are used to quantify the value of pumped storage units in the ancillary services. Since the dispatching schedules of pumped storage units determined the cost of FRR in the TPS, the actual operating experience of pumped storage units studied in this paper can be used to evaluate the impact on the system security and to further define the role of pumped storage units in the ancillary services market. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach based on Weibull distribution to determine the capacity of wind turbine generators (WTGs) using capacity factor (CF), normalized average power (PN), and the product of CF and PN under different values of tower height and rated wind speed. Five locations for installation of WTG in Taiwan are practically examined. The proposed Weibull distribution is employed to represent probability distribution of wind speed variation, while the important relationships among mean wind speed (MWS), standard deviation of wind speed, and both scale and shape parameters of the Weibull distribution are also derived. The cost of energy (COE) and capital costs of WTG under different tower heights and various locations are also determined. It can be concluded from the simulation results of five installation locations of WTG in Taiwan that suitable values for both shape parameter and scale parameters of Weibull distribution as well as wind turbine capacity are identically important for selecting locations of installing WTG. The scale parameter of Weibull distribution also significantly affects COE, and it is important to determine whether a wind farm is good or not. [ABSTRACT FROM AUTHOR]

This paper investigates the power load composition of an isolated power system using a load survey and estimates wind power generation with a probabilistic network. The typical load pattern of various customer classes is derived, which are then used to derive the total power consumption of all customers within each class. A probabilistic neural network is used to solve the win power generation based on the wind speed for an offshore island in Taiwan. With the hourly wind speed and load composition, the power generation of diesel generators was obtained. Results of this paper demonstrate that wind power generation can economically and effectively replace the power generation of the island's diesel power plant and provide partial power-supply capability for the net peak load requirement. [ABSTRACT FROM AUTHOR]

To enhance the cost effectiveness of the distribution automation system (DAS), this paper proposes the immune algorithm (IA) to derive the optimal placement of switching devices by minimizing the total cost of customer service outage and investment cost of line switches. The reliability index of each service zone defined by the boundary switches is derived to solve the expected energy not served due to fault contingency, and the customer interruption cost is then determined according to the customer type and power consumption within the service zone. To demonstrate the effectiveness of proposed IA methodology to solve the optimal placement of line switches, a practical distribution system of Taiwan Power Company (Taipower) is selected for computer simulation to explore the cost benefit of line switch placement for DAS. [ABSTRACT FROM AUTHOR]

This paper proposes an alternative data envelopment analysis method to explore the efficiency, the resource allocation, and the benchmarks of the electricity distribution districts (EDD5) of Taiwan Power Company in 2003. Several empirical results are shown: 1) the EDDs covering the high-tech industry park are more efficient, on average, than ones involved in the nonhigh-tech industry park; 2) the EDDs located in urban areas outperform those located in rural areas; 3) the large-sized EDDs generally are more able to integrate their resources and to operate efficiently; 4) the benchmark-share measure shows that while small-size efficient EDDs can easily become benchmarks, large-size efficient EDDs are deemed as competitive niche players; and finally, 5) the effect on these EDDs merging their activities should be investigated to explore the possibility of increasing competitive advantage in the future. [ABSTRACT FROM AUTHOR]

This paper evaluates the maximum potential rise on the traction earth (TE) conductor caused by stray currents in the Taipei Rail Transit Systems (TRTS). The stray current from the TRTS will flow into the earth due to the voltage difference along the running rails caused by the traction currents returning to the substations. The potential rise of 0.1 V is admitted in international recommendations as the maximum acceptable value for corrosion protection of utilities outside a dc railway system. Since TRTS is one of the dc-traction rail transit systems, it may cause corrosion or other effects by stray currents to the existing underground metallic structures. As a result, the purpose of this paper is to evaluate whether the maximum potential rise on the TE conductor caused by stray currents from IRTS is greater than the maximum permissible value 0.1 V or not. [ABSTRACT FROM AUTHOR]

Rainfall-induced landslides are a major threat in Taiwan, particularly during the typhoon season. A precise survey of landslides after a super event is a critical task for disaster, watershed, and forestry land management. In this paper, we utilize high spatial resolution multispectral optical imagery and a digital elevation model (DEM) with an object-oriented analysis technique to develop a scheme for the recognition of landslides using multilevel segmentation and a hierarchical semantic network. Four case studies are presented to evaluate the feasibility of the proposed scheme. Three kinds of remote sensing imagery, namely pan-sharpened FORMOSAT-2 satellite images, aerial digital images from Z/I digital mapping camera, and images acquired by a digital single lens reflex camera mounted on a fixed-wing unmanned aerial vehicle are used. An accuracy assessment is accomplished by evaluating three test sites containing hundreds of landslides associated with the Typhoon Morakot. The input data include ortho-rectified image and DEM. Four spectral and one topographic object features are derived for semiautomatic landslide recognition. The threshold values are determined semiautomatically by statistical estimation from a few training samples. The experimental results show that the proposed approach can counteract the commission/omission errors and achieve missing/branching factors at less than 0.12 with a quality percentage of 81.7%. The results demonstrate the feasibility and accuracy of the proposed landslide recognition scheme even when different optical sensors are utilized. [ABSTRACT FROM AUTHOR]

This article proposes a fault identification method that is embedded in an asset management system (AMS) to identify the faulted location based on the fault flags reported from the fault indicators (FIs). The fault identification model based on the Petri-net technology is developed using the distribution network topology generated by a geographic information system. The proposed method uses the data set of fault flags generated by FIs, the statuses of circuit breakers, the available precurrent and postcurrent measurements of FIs, and the loadings of distribution feeders and laterals. The hybrid communication system is applied to provide two-way communication between the control center and FIs. The AMS with the embedded fault identification method can dispatch the repair crews to the fault location faster to accelerate the customer service restoration. A distribution feeder of Taiwan Power Company was selected for the computer simulation to demonstrate the effectiveness of the proposed method by using the communication-capable FIs to identify the exact fault location of distribution lines after a short circuit fault occurs in a distribution system. [ABSTRACT FROM AUTHOR]

As the consciousness of human beings in preserving the world increases, the demand of alternative energy resources has been expanding exponentially in recent years, and wind power is one of the most promising renewable energy resources. Taiwan, with its abundant coastal wind resources and good geographical conditions, is very suitable for developing wind farms. The development and implementation of renewable energy regulations have defined a direction for future renewable energy development in Taiwan. This also shows Taiwan's determination to follow the footsteps of the developed countries and the commitment to environmental protection. Therefore, the decision making of wind farms has become the most important link for the construction of wind farms in the future. This paper proposed a fuzzy analytic network process with benefit–opportunity–cost–risk approach to systemize the complicated decision making of wind farm site selection. A case study is carried out to examine the proposed approach and to evaluate the performance of several existing wind farms in Taiwan. By adopting the systematic analysis method, the most suitable wind farm can be determined, and the results can be references for planning and development of wind power industry in the future. [ABSTRACT FROM AUTHOR]

Dynamic capabilities have been widely discussed in the past decade but how the determinants of dynamic capabilities affect a firm's competitive advantage has not been fully explored. This paper develops a quantitative method to investigate how a firm's dynamic capabilities affect a firm's competitive advantage. This study examines the developed hypotheses through a questionnaire survey of 165 firms together with a number of interviews drawn from Taiwan's information and communication technology industry. The results suggest that three determinants of dynamic capabilities (i.e., path, process, and position) influence a technological firm's competitive advantage in different ways. Both position and process have direct positive impacts on firm competitive advantage while position also has a mediating effect on the relationship between process and firm competitive advantage. This paper closes with theoretical and practical implications. [ABSTRACT FROM PUBLISHER]

In this paper, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) using fuzzy time series and automatically generated weights of multiple factors. The proposed method uses the variation magnitudes of adjacent historical data to generate fuzzy variation groups of the main factor (i.e., the TAIEX) and the elementary secondary factors (i.e., the Dow Jones, the NASDAQ and the M1B), respectively. Based on the variation magnitudes of the main factor TAIEX and the elementary secondary factors of a particular trading day, it constructs the occurrence vector of the main factor and the occurrence vectors of the elementary secondary factors on the trading day, respectively. By calculating the correlation coefficients between the numerical data series of the main factor and the numerical data series of each elementary secondary factor, respectively, it calculates the relevance degree between the forecasted variation of the main factor and the forecasted variation of each elementary secondary factor. Based on the correlation coefficients between the numerical data series of the main factor and the numerical data series of each elementary secondary factor on a trading day, it automatically generates the weights of the occurrence vector of the main factor and the occurrence vector of each elementary secondary factor on the trading day, respectively. Then, it calculates the forecasted variation of the main factor and the forecasted variation of each elementary secondary factor on the trading day, respectively, to obtain the final forecasted variation on the trading day. Finally, based on the closing index of the TAIEX on the trading day and the final forecasted variation on the trading day, it generates the forecasted value of the next trading day. The experimental results show that the proposed method outperforms the existing methods. [ABSTRACT FROM PUBLISHER]

The ultimate goal of an electric utility is to create maximum profit while maintaining reliability and security of the power supply. The operation and control of power system is sensitive to system demand. Therefore, improvements in load-forecasting accuracy will lead to cost savings and enhance system security. Due to Taiwan's distinct climate characteristics, it is difficult to obtain satisfactory load-forecasting results by treating the whole island as a single region. In addition, weather factors, such as temperature, relative humidity, and the Heat Index (HI) (a human-perceived equivalent temperature) may also affect load-consumption patterns. This paper proposes a multiregion short-term load-forecasting methodology, taking into account the HI to improve load-forecasting accuracy in Taiwan Power Company's (Taipower's) system. The results show that adopting the HI as a parameter can effectively improve the accuracy if the temperature of the region under investigation is above 27 ^\circ\C (80 ^ \circ\F). By considering both the load/weather diversity and the HI, further improvements to the load forecasting for the Taipower system during summer can be achieved. [ABSTRACT FROM AUTHOR]

Among the ancillary services, a great number of cost allocation strategies have been broadly developed in the deregulated environment. Generally, the utilization of such services can be determined by directly evaluating the actual amount of the usage or by indirectly analyzing the fair/reasonable contribution/attribution to the market participants. In the case of the primary frequency regulation (PFR) service, which is operated by the participating generating units to maintain the real-time balance between the generation and load, the discussion of the PFR service attributed to the load side has still received relatively little attention. In this paper, a new strategy of the cost allocation of the PFR service from the customer side is proposed. Two main factors, the load fluctuation and the frequent demand change, are considered to figure out the PFR reaction relating to the different substations. The design of a scheme for determining the cost allocation index of the PFR service can be applied to the presently exiting power market. In addition, the actually load series recorded from the extra-high voltage (EHV) substations of the Taipower system located in northern, central, and southern Taiwan are meticulously analyzed and utilized to verify the feasibility and practicability of cost allocation. [ABSTRACT FROM AUTHOR]

In this paper, an expert system is designed to derive the rephasing strategy of laterals and distribution transformers to enhance three-phase balancing of distribution systems. The heuristic rules adopted by distribution engineers are incorporated in the knowledge base of the expert system in the problem-solving process. The neutral current reduction algorithm is developed to support the inference engine to derive the rephasing strategy to reduce the neutral current of distribution feeder so that the tripping of over-current relay can be prevented and the customer service interruption cost and labor cost to execute the rephasing strategy can be justified by the power loss reduction obtained. To demonstrate the effectiveness of the proposed expert system to enhance three-phase balance, a practical distribution feeder in Taiwan Power Company (Taipower) is selected for computer simulation. By minimizing the objective function subjected to the rephasing rules, the rephasing strategy has been derived to identify the laterals and distribution transformers for phasing adjustment. After executing the proposed rephasing strategy by Taipower engineers, the phase currents and neutral current of test feeder has been collected by the SCADA system to verify the reduction of neutral current. The power loss reduction obtained by three-phase balancing has been solved by three-phase load flow analysis, which is then used to justify the customer service interruption cost and labor cost for rephasing of test feeder. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy set based modeling of wind power generation. The wind power generation has been solved by the proposed fuzzy generation for an island in Taiwan. The cost effectiveness of wind power generation is then evaluated by calculating the avoided generation cost of diesel generators. The load survey study has been performed to find the typical daily load patterns of various customer classes. With the typical load patterns and total energy consumption by each customer class, the load composition and daily power profile of the isolated power system are therefore derived. The wind power generation of eight wind turbines and the corresponding avoided generation cost is estimated by the fuzzy generation model according to the hourly wind speed. The power generation and the corresponding cost of diesel generators required to meet the system power demand with wind power generation have therefore been obtained. It is found that the wind power generation can economically and effectively substitute the generation cost of the diesel power plant and provide the partial power supply capability for the net peak load demand. [ABSTRACT FROM AUTHOR]

This paper describes the application of proposed under-frequency load shedding scheme with dynamic D-factors, i.e., load frequency and voltage dependent coefficients, of various dynamic load models to Taiwan power system. The load models adopted are 1) a single-motor dynamic model, 2) a two motor (one small and one large) dynamic model, and 3) a composite (static and dynamic) model. First, the dynamic D -factor values of these load models are determined by the actual analytical approach employed in Taiwan power system. Then, a single-machine model representing a multi-machine power system is utilized for validating the proposed load shedding scheme with derived dynamic D-factor values. Finally, time simulation results of load shedding applied to various load models are compared with field measurement data, which are obtained from Taiwan power system in the case of three-phase short circuit fault, to evaluate the effects of different load models on the proposed load shedding scheme, based on the restoration of system frequency. [ABSTRACT FROM AUTHOR]

This paper presents a practical case for the safety assessment of ground grid design at 161/69-kV indoor-type and out- door-type substations in the system of Taiwan Power Company (TPC). For a substation grounding system to be safe, the touch and step voltages should be limited below the minimum tolerable voltages. Since the mesh voltage is usually the worst possible touch voltage inside an ac substation (excluding transferred potentials), the mesh voltage is used as the criteria for a safe ground grid design. In other words, safety assessment of a ground grid design at 161/69-kV indoor-type and outdoor-type substations in the TPC system is referred to as a procedure by which the mesh and step voltages at substations are computed and compared to the minimum touch and step voltages. Computation results of safety assessment for humans with 50- and 70-kg body weight are quantified in this paper. [ABSTRACT FROM AUTHOR]

This paper presents the effects of rain on the performance of a Ka-band local multipoint distribution system (LMDS) in Taiwan. The rain distribution statistics, from 2-yr measurements with 1-mm temporal resolution and 12-yr measurements with a 1-h temporal resolutions, were analyzed. The rain-attenuation model that takes local rain effects is established statistically. These statistical data are used to analyze the performance of the LMDS in terms of its signal-to-interference (S/I) ratio, bit-error rate (HER), and channel capacity at various service distances. From the analysis, it is found that the light rain events induce better S/I for cellWar network service, because other base transceiver station (Hi'S) interference signals around the main BTS are likely to be blocked by rain. The probability that below the nominal value of the channel capacity, when there is rain fading without cellular interference, meets a margin of HER = 10-6 in a 6-km cell using quaternary phase-shift keying (QPSK) modulation. However, when the cellular interference is presented, the effective BTS service distance greatly shrinks to 2-3 km. In summary, in a cellular network environment, as the cell coverage radius is reduced, the effective BTS service range will be correspondingly compressed, suggesting that the cellular interference is even more serious than the rain attenuation itself. [ABSTRACT FROM AUTHOR]

The isolated power system in Kinmen Island, Taiwan has already implemented the special protection system (SPS) to prevent various critical contingencies that occurred during the past decade. However, when a severe N-2 contingency occurred on July 26, 2013, the SPS has not properly armed its under-frequency load shedding. After reexamining transient recorded waveforms, it was observed that the system still has sufficient spinning reserve and the coordination between the under-frequency relay and the current SPS was not well considered. In this article, the current SPS is further modified in order to avoid the occurrence of the excessive load shedding under similar N-2 contingencies. Extensive time-domain dynamical simulations are performed first to study the relationship between the amount of the load shedding and frequency deviations under these extreme N-2 contingencies. Based on these simulation results, the remediation scheme of the SPS will be proposed by modifying the existing SPS design logic and the amount of load shedding. More comprehensive input triggered states are proposed for identifying these severe N-2 contingencies. Both simulation verifications under the proposed remedial scheme and actual transient recorded waveforms under a severe contingency after commissioning this remediated SPS are provided to demonstrate the effectiveness of this proposed remediation scheme. [ABSTRACT FROM AUTHOR]

The penetration of renewable energy is gradually increasing. Therefore, power system flexibility, which is required to maintain system security and to cope with renewable generation uncertainty, becomes more important. Various technologies, such as flexible generators, demand management, energy storage, network reconfiguration, and even efficient system operations, are capable of improving power system flexibility. Nevertheless, among them, flexible generation resources can provide a direct way to enhance the power system flexibility. This article first applies the fuzzy analytic hierarchy process to calculate the flexibility index of generation resources. Then, the process of unit scheduling is implemented under various operation scenarios to investigate the relationship between the generation flexibility and the cost of unit scheduling. Finally, the required flexibility and the corresponding capacity of flexible generators under a specified penetration of renewable power generation are investigated under different operation scenarios. [ABSTRACT FROM AUTHOR]

Electric load analysis is an important task in early new stage for design of shipboard power systems (SPSs). The installation generation capacity onboard depends on the accurate result of the analysis, which significantly affects the system economic and secure operations. In the traditional electrical load analysis, the demand factor is often obtained from engineering experiences which may lead to inaccurate analysis results. In order to obtain better results, a methodology for electrical load analysis in SPSs is proposed in this article. The load analysis spreadsheet is adopted to find the power consumption of key electric loads in SPSs. The actual power consumptions of selected loads are collected by intelligent meters. The statistical analysis is then performed to find the critical parameter of each selected load in the load analysis under different operating conditions based on the power measurement of field test and load analysis is performed for estimating system power demand accordingly. The large practical maritime vessel power systems are selected for numerical analysis to ensure the performance of the proposed method. The proposed method has been adopted by local ship builders in Taiwan to better understand the load characteristics in shipboard power systems to support various functions of system planning and operation in a more effective manner. [ABSTRACT FROM AUTHOR]