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This research studies the characteristics of ocean current meanders from the viewpoint of power generation engineering and the potential of maximizing ocean current power generation capacity by making generator turbines to track the meanders applying a recently proposed Cross-stream Active Mooring concept. The current meanders will hurt capacity factor of marine turbines moored at fixed locations, somewhat like the issue of wind availability for wind farms. The new mooring concept features a hydro sail system that can deploy generator turbines transversely across streams in a marine current. The hydro sail system can further adjust the horizontal position of the turbines, by changing sail angle of attack, to actively track fast streams in an ocean current. This paper first reviews and discusses the characteristics of short-term track variations of the Florida Current and the Kuroshio near Taiwan and then analyzes potential improvement in power generation using measured and simulated current velocity data in the two ocean currents, suggesting a potential increase of 10–40 % power generation achievable by tracking the meanders. Operations of the hydro sail were demonstrated by tests using remote controllable and passive scale models. Control methods are discussed. Approaches to observe, predict and track the meanders are conceptualized. [ABSTRACT FROM AUTHOR]

This research studies the characteristics of ocean current meanders from the viewpoint of power generation engineering and the potential of maximizing ocean current power generation capacity by making generator turbines to track the meanders applying a recently proposed Cross-stream Active Mooring concept. The current meanders will hurt capacity factor of marine turbines moored at fixed locations, somewhat like the issue of wind availability for wind farms. The new mooring concept features a hydro sail system that can deploy generator turbines transversely across streams in a marine current. The hydro sail system can further adjust the horizontal position of the turbines, by changing sail angle of attack, to actively track fast streams in an ocean current. This paper first reviews and discusses the characteristics of short-term track variations of the Florida Current and the Kuroshio near Taiwan and then analyzes potential improvement in power generation using measured and simulated current velocity data in the two ocean currents, suggesting a potential increase of 10–40 % power generation achievable by tracking the meanders. Operations of the hydro sail were demonstrated by tests using remote controllable and passive scale models. Control methods are discussed. Approaches to observe, predict and track the meanders are conceptualized. [ABSTRACT FROM AUTHOR]

This is a discussion on the paper titled “Assessing feed-in tariffs on wind power installation and industry development in Taiwan” published by Hsu et al. In the discussed paper, there were several missing variables in the historical test of the system dynamics (SD) model, and thus the test was not integrated and valid. Additionally, the simulated results of the missing variables were used as important indexes to observe the behavior of the SD model. Therefore, it was highly likely that the solution and related policy analysis based on the simulated results were incorrect. Accordingly, the present study illustrated the structure characteristics of the SD model with respect to the fore-mentioned problems, discussed the reason for missing variables and proposed a method to assess whether or not the historical test was integrated. Finally, after a careful analysis, this study offered suggestions to perfect the historical test proposed in the discussed paper. [ABSTRACT FROM AUTHOR]

This paper presents a performance analysis of predictive models for the generator module which can be used as a reference for improvement in the condition monitoring system using wind turbines in a wind farm in Taiwan. With the generator being a critical component prone to failures, it is important to perform data analysis on its parameters that could be used for condition monitoring. The main innovative feature in this framework is the conduct of performance analysis before the development of the condition monitoring system. Also, the consistency of the performance between the different wind turbines in the wind farm is evaluated. The predictive models are generated using the neural network algorithm with a different combination of parameters from the SCADA system. The correlation of the parameters as well as the mean square error of the predictive models were then computed for analysis. Results showed that pairing of input parameters with a higher correlation to the output parameter would give better performance for the predictive model. Furthermore, the performance of the different models was consistent throughout the different wind turbines in the wind farm which indicates that the same model can be developed and used for wind turbines belonging to the same wind farm. Employing a preliminary performance analysis of different combinations of component parameters could help in optimizing predictive models for condition monitoring. [ABSTRACT FROM AUTHOR]