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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]

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]

This paper proposes a novel approach to the generation of Chinese sentences from ill-formed Taiwanese Sign Language (TSL) for people with hearing impairments. First, a sign icon-based virtual keyboard is constructed to provide a visualized interface to retrieve sign icons from a sign database. A proposed language model (LM), based on a predictive sentence template (PST) tree, integrates a statistical variable n-gram LM and linguistic constraints to deal with the translation problem from ill-formed sign sequences to grammatical written sentences. The PST tree trained by a corpus collected from the deaf schools was used to model the correspondence between signed and written Chinese. In addition, a set of phrase formation rules, based on trigger pair category, was derived for sentence pattern expansion. These approaches improved the efficiency of text generation and the accuracy of word prediction and, therefore, improved the input rate. For the assessment of practical communication aids, a reading-comprehension training program with ten profoundly deaf students was undertaken in a deaf school in Tainan, Taiwan. Evaluation results show that the literacy aptitude test and subjective satisfactory level are significantly improved.

In this paper, we develop an intercity bus scheduling model for a variable market share. The proposed model, unlike the past intercity bus scheduling models, does not assume a fixed market share. Instead, passenger choice behaviors in competitive markets are considered. The model is formulated as a nonlinear mixed integer program that is characterized as nondeterministic polynomial-time hard. We develop a solution algorithm to efficiently solve the model. The test results, which are based on a major Taiwan intercity bus carrier, show the good performance of the model and the solution algorithm. [ABSTRACT FROM AUTHOR]

The coevolutionary algorithm (CEA) based on the Lagrangian method is proposed for hydrothermal generation scheduling. The main purpose of hydrothermal generation scheduling is to minimize the overall operation cost and the constraints satisfied by scheduling the power outputs of all hydro and thermal units under study periods, given electrical load and limited water re- source. In the proposed method, a genetic algorithm is successfully incorporated into the Lagrangian method. The genetic algorithm searches out the optimum using multiple-path techniques and possesses the ability to deal with continuous and discrete variables. Regardless of the objective function characteristic the genetic algorithm does not have to modify the design rules and possesses the ability to go over local solutions toward the global optimal solution. The genetic algorithm can improve the disadvantages of the traditional Lagrangian method, which updates Lagrange multipliers according to the degree of system constraint violation by the gradient algorithm, and further searches out the global optimal solution. The developed algorithm is illustrated and tested on a practical Taiwan power system. Numerical results show that the proposed CEA based on the Lagrangian method is a very effective method for searching out the global optimal solution. [ABSTRACT FROM AUTHOR]

Presents an accurate dynamic load estimation (DLE) algorithm capable of achieving the balance impact on the grid while providing a complete coverage of all the principles and parameters used during the derivation. Evaluation of the unbalanced impact of the Taiwan high-speed railway (HSR); Application of the proposed DLE algorithm; Traction power system structure of Taiwan's HSR system.

Restructuring of power system stresses the need for economic and reliable generation of power. Therefore generating units should be committed considering fuel cost and reliability level of the system. This necessitates the need for multi-objectives to be met in a unit commitment problem (UCP). Since the above objectives are conflicting in nature, a novel methodology employing optimal deviation based firefly algorithm tuned fuzzy membership function is applied to multi-objective unit commitment problem (MOUCP). The ON/OFF status of the generating units is obtained by binary coded FF whereas the sub-problem economic dispatch (ED) is obtained by real coded FF. Here the conflicting functions are formulated as a single objective function using fuzzy weighted optimal deviation. The fuzzy membership design variables are tuned using real coded FF; thereby the requirement of expertise for setting these variables are eliminated. The proposed methodology is validated on 100-unit system, IEEE RTS 24-bus system, IEEE 118-bus system and a practical Taiwan Power (Taipower) 38-unit system over a 24-h period. Effective strategy on scheduling spinning reserve is demonstrated by comparing its performance with other methods reported in the literature. [ABSTRACT FROM PUBLISHER]