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Featured researches published by Ming-Tang Tsai.


Expert Systems With Applications | 2011

An efficient hybrid Taguchi-immune algorithm for the unit commitment problem

Whei-Min Lin; Hong-Jey Gow; Ming-Tang Tsai

In this paper, a hybrid Taguchi-immune algorithm (HTIA) is presented to deal with the unit commitment problem. HTIA integrates the Taguchi method and the traditional immune algorithm (TIA), providing a powerful global exploration capability. Taguchi method (TM) has been widely used in experimental designs for problems with multiple parameters, and is incorporated into TIA in this paper for the crossover operation to select a better gene. The effectiveness and efficiency of HTIA are demonstrated by several case studies, and the results are compared with other methods published before. Test results show that the proposed method is feasible, robust, and more effective than many other previously developed computation algorithms.


Expert Systems With Applications | 2011

Hybridizing Particle Swarm Optimization with Signal-to-Noise Ratio for numerical optimization

Whei-Min Lin; Hong-Jey Gow; Ming-Tang Tsai

Abstract This paper hybridized the Particle Swarm Optimization (PSO) with Signal-to-Noise Ratio (SNR) to solve the numerical optimization problems. PSO has the ability of both global and local searches, where improper parameter settings could cause the algorithm to converge at the local optimum. SNR, on the other hand, has the ability to evaluate “existence possibility of optimal value”. Integration of PSO and SNR thus becomes more robust, statistically sound and efficient than PSO. In this paper, fifteen standard test functions (benchmark problems) with a large number of local optimal solutions and high dimension (30 or 100 dimension) are used for examples and solved by the proposed algorithm. The results show that the proposed algorithm by this study can effectively obtain the global optimal solutions or close-to-optimal solutions.


Archive | 2014

The Optimal Placement of Wind Turbine in a Distribution System

Ming-Tang Tsai; Sung-Ling Chen; Szu-Wzi Wu; Cheng-Pin Lin

This paper presents an approach for determining optimal placement of wind turbine in the distribution systems. In order to minimize the system losses the optimization approach is solved by the Particle Swarm Optimization (PSO). To enhance the performance of the optimization approach, a load flow model with Equivalent Current Injection (ECI) is used to analyze the power flow of distribution systems for getting better convergent characteristics. Example of Taipower distribution feeder is presented to illustrate the efficiency and feasible of the proposed algorithm. Simulation results show that with proper placement of wind turbine can be used to reduce system loss, and maintain the voltage profile.


Applied Energy | 2010

An enhanced radial basis function network for short-term electricity price forecasting

Whei-Min Lin; Hong-Jey Gow; Ming-Tang Tsai


Energy Conversion and Management | 2010

Electricity price forecasting using Enhanced Probability Neural Network

Whei-Min Lin; Hong-Jey Gow; Ming-Tang Tsai


Energy Conversion and Management | 2011

Combining of Direct Search and Signal-to-Noise Ratio for economic dispatch optimization

Whei-Min Lin; Hong-Jey Gow; Ming-Tang Tsai


Energies | 2015

Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization

Whei-Min Lin; Chia-Sheng Tu; Ming-Tang Tsai


International Journal of Electrical Power & Energy Systems | 2011

A novel stochastic search method for the solution of economic dispatch problems with non-convex fuel cost functions

Ming-Tang Tsai; Hong-Jey Gow; Whei-Min Lin


Applied Energy | 2011

The influence of carbon dioxide trading scheme on economic dispatch of generators

Ming-Tang Tsai; Chih-Wei Yen


International Journal of Electrical Power & Energy Systems | 2011

Hybrid Taguchi-Immune Algorithm for the thermal unit commitment

Ming-Tang Tsai; Hong-Jey Gow; Whei-Min Lin

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Whei-Min Lin

National Sun Yat-sen University

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Hong-Jey Gow

National Sun Yat-sen University

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Chia-Sheng Tu

National Sun Yat-sen University

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Ren-Fu Yang

National Sun Yat-sen University

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