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    Improved fuel-use efficiency in diesel–electric tugboats with an asynchronous power generating unit
    (IEEE Transactions On Transportation Electrification, 2019) Anil Kumar, Birudula; Raghu, Selvaraj; Thanga Raj, Chelliah; Ramesh, U. S.
    High capacity diesel–electric tugboats are employed at every modernized harbor for assisting big marine vessels and other harbor applications. Contemporary tugboats use multiple power sources to meet their propulsion and auxiliary on-board load demands. The effective utilization of multiple power sources leads to better fuel use efficiency with reduced emissions, economic, and environmental benefits. This paper presents a simple optimization technique for scheduling available power sources of a diesel–electric tugboat [diesel engine generators (DEGs) and batteries] to meet its load demand with an objective to minimize fuel consumption. For this paper, a diesel–electric tugboat system of 1.1-MW capacity with different generating systems is considered: 1) fixed speed generating unit (2 × 550 kW fixed speed DEG employing synchronous generators) and 2) variable speed generating unit [1×1.1 MWvariable speed DEG employing doubly fed induction generator (DFIG)]. From the optimized test results, it is inferred that the variable speed generating unit offers a fuel saving of 29.86% in comparison with diesel-mechanical propelled system and 2.9%in comparison with fixed speed diesel– electric system. The simulation of a 1.1-MW variable speed generating system is performed in MATLAB/Simulink 2014A environment, and experimental demonstration is performed through a 2.2-kW laboratory prototype
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    Optimization of a hydro kinetic power generator using genetic algorithm
    (Spingerlink, 2021-12-27) Viswanath, Anjana; Chandran, Vidya; Janardhanan, Sheeja
    The paper discusses the optimization of a renewable energy harvester which converts kinetic energy of slow moving currents into electricity. The metaheuristic method of genetic algorithm is adopted to optimize the process parameters of the Hydro Vortex Power Generator (HVPG). The study is conducted in a three folded manner. The device was optimized for the range of Reynolds number 0.3 × 105 < Re < 2.5 × 105 based on equations derived analytically from vibration theory and then using an empirical equation derived from experimental data for two regimes of flow (250 < Re < 3.8 × 104 and 0.3 × 105 < Re < 2.5 × 105. Empirical optimization model is observed to predict the maximum amplitude of oscillation with in a realistic range with the theoretical model showing a three time over prediction. A comparison with experimental results suggests that the effect of added mass on the amplitude of oscillation is of enhanced damping and hence a more realistic prediction is obtained from empirical model optimization. The most significant result from this analysis is that the empirical model predicts maximum amplitude at lowest value of mass ratio (m*), whereas the theoretical model predicts it at the highest value.