Conference Proceedings

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Subject: search.filters.subject.Optimization

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    Control strategy for fuel saving in asynchronous generator driven electric tugboats
    (IEEE, 2016-12) Anil Kumar, B.; Anil Kumar, K.; Radha, T.; Chelliah, Thanga Raj; Khare, Deepak; Ramesh, U. S.
    Usually electric tugboats are equipped with diesel engine based electric generator for power production, battery for supplying power to auxiliary loads and electric motors for propulsion. This paper proposes control strategies for diesel engine and electric generators used in electric tugboat to improve energy efficiency of the system. Doubly fed induction machine (DFIM), asynchronous in nature, is considered in this research which serves as generator (power production). The speed of diesel engine is controlled in accordance with the power demanded by the tug. Output voltage and frequency of generator during sub-synchronous operation are regulated by controlling its rotor current with the help of power electronic convertors. Comparison of fuel consumption at fixed and variable speeds of operation is performed. From the test results, it is observed that the variable speed operation of diesel generator offers significant reduction in fuel consumption.
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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.