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Dr. Chao-Rong Chen
Department of Electrical Engineering, National Taipei University of Technology, Taipei 106, Taiwan

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0 Artificial Intelligence
0 Neural Networks
0 Power Systems
0 Smart Grid
0 Swarm Intelligence

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Journal article
Published: 08 July 2021 in Energies
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The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines’ layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines’ layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.

ACS Style

Yi-Zeng Hsieh; Shih-Syun Lin; En-Yu Chang; Kwong-Kau Tiong; Shih-Wei Tan; Chiou-Yi Hor; Shyi-Chy Cheng; Yu-Shiuan Tsai; Chao-Rong Chen. Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm. Energies 2021, 14, 4125 .

AMA Style

Yi-Zeng Hsieh, Shih-Syun Lin, En-Yu Chang, Kwong-Kau Tiong, Shih-Wei Tan, Chiou-Yi Hor, Shyi-Chy Cheng, Yu-Shiuan Tsai, Chao-Rong Chen. Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm. Energies. 2021; 14 (14):4125.

Chicago/Turabian Style

Yi-Zeng Hsieh; Shih-Syun Lin; En-Yu Chang; Kwong-Kau Tiong; Shih-Wei Tan; Chiou-Yi Hor; Shyi-Chy Cheng; Yu-Shiuan Tsai; Chao-Rong Chen. 2021. "Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm." Energies 14, no. 14: 4125.

Journal article
Published: 12 July 2020 in Sustainability
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Under the vigorous development of global anticipatory computing in recent years, there have been numerous applications of artificial intelligence (AI) in people’s daily lives. Learning analytics of big data can assist students, teachers, and school administrators to gain new knowledge and estimate learning information; in turn, the enhanced education contributes to the rapid development of science and technology. Education is sustainable life learning, as well as the most important promoter of science and technology worldwide. In recent years, a large number of anticipatory computing applications based on AI have promoted the training professional AI talent. As a result, this study aims to design a set of interactive robot-assisted teaching for classroom setting to help students overcoming academic difficulties. Teachers, students, and robots in the classroom can interact with each other through the ARCS motivation model in programming. The proposed method can help students to develop the motivation, relevance, and confidence in learning, thus enhancing their learning effectiveness. The robot, like a teaching assistant, can help students solving problems in the classroom by answering questions and evaluating students’ answers in natural and responsive interactions. The natural interactive responses of the robot are achieved through the use of a database of emotional big data (Google facial expression comparison dataset). The robot is loaded with an emotion recognition system to assess the moods of the students through their expressions and sounds, and then offer corresponding emotional responses. The robot is able to communicate naturally with the students, thereby attracting their attention, triggering their learning motivation, and improving their learning effectiveness.

ACS Style

Yi-Zeng Hsieh; Shih-Syun Lin; Yu-Cin Luo; Yu-Lin Jeng; Shih-Wei Tan; Chao-Rong Chen; Pei-Ying Chiang. ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation. Sustainability 2020, 12, 5605 .

AMA Style

Yi-Zeng Hsieh, Shih-Syun Lin, Yu-Cin Luo, Yu-Lin Jeng, Shih-Wei Tan, Chao-Rong Chen, Pei-Ying Chiang. ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation. Sustainability. 2020; 12 (14):5605.

Chicago/Turabian Style

Yi-Zeng Hsieh; Shih-Syun Lin; Yu-Cin Luo; Yu-Lin Jeng; Shih-Wei Tan; Chao-Rong Chen; Pei-Ying Chiang. 2020. "ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation." Sustainability 12, no. 14: 5605.

Journal article
Published: 08 February 2017 in Energies
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This paper proposes a novel methodology for very short term forecasting of hourly global solar irradiance (GSI). The proposed methodology is based on meteorology data, especially for optimizing the operation of power generating electricity from photovoltaic (PV) energy. This methodology is a combination of k-nearest neighbor (k-NN) algorithm modelling and artificial neural network (ANN) model. The k-NN-ANN method is designed to forecast GSI for 60 min ahead based on meteorology data for the target PV station which position is surrounded by eight other adjacent PV stations. The novelty of this method is taking into account the meteorology data. A set of GSI measurement samples was available from the PV station in Taiwan which is used as test data. The first method implements k-NN as a preprocessing technique prior to ANN method. The error statistical indicators of k-NN-ANN model the mean absolute bias error (MABE) is 42 W/m2 and the root-mean-square error (RMSE) is 242 W/m2. The models forecasts are then compared to measured data and simulation results indicate that the k-NN-ANN-based model presented in this research can calculate hourly GSI with satisfactory accuracy.

ACS Style

Chao-Rong Chen; Unit Three Kartini. k-Nearest Neighbor Neural Network Models for Very Short-Term Global Solar Irradiance Forecasting Based on Meteorological Data. Energies 2017, 10, 186 .

AMA Style

Chao-Rong Chen, Unit Three Kartini. k-Nearest Neighbor Neural Network Models for Very Short-Term Global Solar Irradiance Forecasting Based on Meteorological Data. Energies. 2017; 10 (2):186.

Chicago/Turabian Style

Chao-Rong Chen; Unit Three Kartini. 2017. "k-Nearest Neighbor Neural Network Models for Very Short-Term Global Solar Irradiance Forecasting Based on Meteorological Data." Energies 10, no. 2: 186.

Journal article
Published: 01 November 2016 in International Journal of Electrical Power & Energy Systems
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Uninterruptible power systems in hydro plants under the surge environment of high exposure are susceptible to surge impact. In order to solve the problems of equipment malfunctions or failures caused by the surge, this paper applies the principle of surge energy transfer to design a low-voltage surge protection circuit, which prevents the surge from interfering with or damaging UPS devices. According to the IEEE and IEC standards test requirements, after the actual loads are connected to the load side of this circuit, surge generators are used to test the surge immunity of the surge protection circuit and actual load; test results confirm that the surge protection circuit proposed in this paper is effective for the protection of surge interference at low-voltage.

ACS Style

Chao-Rong Chen; Mu-Cheng Chen; Chih-Ju Chou; Chun-Yao Lee; Chun-Chi Chen. Promoting the surge immunity techniques of an uninterruptible hydro plant power system under the surge environment of high exposure. International Journal of Electrical Power & Energy Systems 2016, 82, 274 -280.

AMA Style

Chao-Rong Chen, Mu-Cheng Chen, Chih-Ju Chou, Chun-Yao Lee, Chun-Chi Chen. Promoting the surge immunity techniques of an uninterruptible hydro plant power system under the surge environment of high exposure. International Journal of Electrical Power & Energy Systems. 2016; 82 ():274-280.

Chicago/Turabian Style

Chao-Rong Chen; Mu-Cheng Chen; Chih-Ju Chou; Chun-Yao Lee; Chun-Chi Chen. 2016. "Promoting the surge immunity techniques of an uninterruptible hydro plant power system under the surge environment of high exposure." International Journal of Electrical Power & Energy Systems 82, no. : 274-280.

Journal article
Published: 02 December 2014 in IEEE Transactions on Power Delivery
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Currently, self-healing is one of the most important functions in the smart grid. Meanwhile, fault detection, isolation, and restoration of feeder automation systems dominate the self-healing function in power distribution systems. The steps of the aforementioned function depend on the fault flag status of the feeder terminal unit. The conditions for setting this flag are judged by the feeder terminal unit overcurrent detecting curve. This paper found an efficient approach to calculate this curve via a half-interval method. Versatile application software with the curve plotting capability was also developed and deployed on the web server of the information-management department of Taiwan Power Company and is running successfully.

ACS Style

Chao-Rong Chen; Chi-Juin Chang. Half Interval Method Applied in Feeder Terminal Unit Overcurrent Detecting Curve Setting. IEEE Transactions on Power Delivery 2014, 30, 1 -1.

AMA Style

Chao-Rong Chen, Chi-Juin Chang. Half Interval Method Applied in Feeder Terminal Unit Overcurrent Detecting Curve Setting. IEEE Transactions on Power Delivery. 2014; 30 (4):1-1.

Chicago/Turabian Style

Chao-Rong Chen; Chi-Juin Chang. 2014. "Half Interval Method Applied in Feeder Terminal Unit Overcurrent Detecting Curve Setting." IEEE Transactions on Power Delivery 30, no. 4: 1-1.

Research article
Published: 16 July 2014 in International Journal of Photoenergy
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Demand response (DR) is used mainly to help to schedule a customer’s power utilization based on the electricity price that is announced by the power distribution company so that both demand and supply can optimally benefit. The work proposes a users’ load model and the interior point method for optimal scheduling with elastic power utilization to minimize power price. The interior point method has the advantages of rapid convergence and robustness. Customers can not only use PV generators and battery sets as backup power sources, but also benefit from green energy. As revealed by the results herein, the use of elastic power utilization time intervals enables customers to pay less power price.

ACS Style

Chao-Rong Chen; Ming-Jen Lan. Optimal Demand Response of Smart Home with PV Generators. International Journal of Photoenergy 2014, 2014, 1 -9.

AMA Style

Chao-Rong Chen, Ming-Jen Lan. Optimal Demand Response of Smart Home with PV Generators. International Journal of Photoenergy. 2014; 2014 ():1-9.

Chicago/Turabian Style

Chao-Rong Chen; Ming-Jen Lan. 2014. "Optimal Demand Response of Smart Home with PV Generators." International Journal of Photoenergy 2014, no. : 1-9.

Journal article
Published: 27 January 2014 in IEEJ Transactions on Electrical and Electronic Engineering
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This paper proposes the optimal planning of soft starter characteristics for a large drain motor based on simulated annealing (SA). First, the planning of the soft starter characteristics is formulated as an optimization problem with minimal motor starting time; then, the constraints of the motor starting energy, power quality requirements, and minimal cost of transmission line are constructed. The system framework of an actual case in Taiwan is used as the basis of this study with simulation. Before and after the installation of three sets of soft starters, measuring instruments are used in the field to investigate the changes of current and voltage during the motor starting, thus establishing the database of current swell and voltage sag. The searching algorithm based on the SA method is developed by the program MATLAB, such that the soft starter can regulate the minimal motor starting time and meet the above‐mentioned constraints. According to the model of the system circuit and the characteristic parameters constructed by an actual case, the simulation results verify the superiority of the proposed SA method. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

ACS Style

Chih-Ju Chou; Chun-Yao Lee; Chun-Chi Chen; Chao-Rong Chen; Mu-Cheng Chen. Optimal planning of soft starter for large drain motor based on simulated annealing method. IEEJ Transactions on Electrical and Electronic Engineering 2014, 9, 136 -143.

AMA Style

Chih-Ju Chou, Chun-Yao Lee, Chun-Chi Chen, Chao-Rong Chen, Mu-Cheng Chen. Optimal planning of soft starter for large drain motor based on simulated annealing method. IEEJ Transactions on Electrical and Electronic Engineering. 2014; 9 (2):136-143.

Chicago/Turabian Style

Chih-Ju Chou; Chun-Yao Lee; Chun-Chi Chen; Chao-Rong Chen; Mu-Cheng Chen. 2014. "Optimal planning of soft starter for large drain motor based on simulated annealing method." IEEJ Transactions on Electrical and Electronic Engineering 9, no. 2: 136-143.

Original articles
Published: 29 June 2011 in Electric Power Components and Systems
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Conventional optimization methods for approaching overcurrent relay settings focus on minimizing the operating time of total relays at maximum fault current to accelerate the fault clearance time. However, to judge whether the entire relay curve of each relay pair always meets the constraints of 0.2 or 0.3 sec to the object curve is rather difficult as the curves may have different slopes. Additionally, the coordination time at the closest position for the curves of a relay pair should be checked for coordination validation. Therefore, this work presents a novel partial differentiation approach method to ensure that the curves of overcurrent relay coordination do not intersect with each other and violate the coordination time interval. Relay setting values are normally plotted on the time-current plane to verify the closing or intersection between relay pairs. Thus, a computer program based on the partial differentiation approach is also developed to calculate the current value of the intersection or closest position. Furthermore, a case study involving an industrial power system demonstrates the effectiveness of the proposed method by validating the results of optimization relay coordination.

ACS Style

Chao-Rong Chen; Cheng Hung Lee; Chi-Juin Chang. Overcurrent Relay Coordination Optimization with Partial Differentiation Approach for the Validation of Coordination Violation. Electric Power Components and Systems 2011, 39, 933 -947.

AMA Style

Chao-Rong Chen, Cheng Hung Lee, Chi-Juin Chang. Overcurrent Relay Coordination Optimization with Partial Differentiation Approach for the Validation of Coordination Violation. Electric Power Components and Systems. 2011; 39 (10):933-947.

Chicago/Turabian Style

Chao-Rong Chen; Cheng Hung Lee; Chi-Juin Chang. 2011. "Overcurrent Relay Coordination Optimization with Partial Differentiation Approach for the Validation of Coordination Violation." Electric Power Components and Systems 39, no. 10: 933-947.

Journal article
Published: 31 January 2009 in Energy Conversion and Management
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This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems.

ACS Style

Yung-Chung Chang; Ching-Yin Lee; Chao-Rong Chen; Chih-Ju Chou; Wen-Hui Chen; Wu-Hsing Chen. Evolution strategy based optimal chiller loading for saving energy. Energy Conversion and Management 2009, 50, 132 -139.

AMA Style

Yung-Chung Chang, Ching-Yin Lee, Chao-Rong Chen, Chih-Ju Chou, Wen-Hui Chen, Wu-Hsing Chen. Evolution strategy based optimal chiller loading for saving energy. Energy Conversion and Management. 2009; 50 (1):132-139.

Chicago/Turabian Style

Yung-Chung Chang; Ching-Yin Lee; Chao-Rong Chen; Chih-Ju Chou; Wen-Hui Chen; Wu-Hsing Chen. 2009. "Evolution strategy based optimal chiller loading for saving energy." Energy Conversion and Management 50, no. 1: 132-139.

Conference paper
Published: 01 November 2007 in 2007 International Conference on Intelligent Systems Applications to Power Systems
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In this paper a modified genetic algorithm is used to perform the IDMT overcurrent relay coordination applied in an industrial plant radial power distribution system for quickly getting the result of the best coordination comparing with the computer-aided software of traditional method. The result shows that it is fast and adoptable compared to the traditional method by verifying with an existing power system settings.

ACS Style

Cheng-Hung Lee; Chao-Rong Chen. Using Genetic Algorithm for Overcurrent Relay Coordination in Industrial Power System. 2007 International Conference on Intelligent Systems Applications to Power Systems 2007, 1 -5.

AMA Style

Cheng-Hung Lee, Chao-Rong Chen. Using Genetic Algorithm for Overcurrent Relay Coordination in Industrial Power System. 2007 International Conference on Intelligent Systems Applications to Power Systems. 2007; ():1-5.

Chicago/Turabian Style

Cheng-Hung Lee; Chao-Rong Chen. 2007. "Using Genetic Algorithm for Overcurrent Relay Coordination in Industrial Power System." 2007 International Conference on Intelligent Systems Applications to Power Systems , no. : 1-5.