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Energy Consumption Analysis and Optimization of the Deep-Sea Self-Sustaining Profile Buoy

机译:深海自我维持型材浮标的能耗分析与优化

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摘要

In order to reduce the energy consumption of deep-sea self-sustaining profile buoy (DSPB) and extend its running time, a stage quantitative oil draining control mode has been proposed in this paper. System parameters have been investigated including oil discharge resolution (ODR), judgment threshold of the floating speed and frequency of oil draining on the energy consumption of the system. The single-objective optimization model with the total energy consumption of DSPB’s ascent stage as the objective function has been established by combining the DSPB’s floating kinematic model. At the same time, as the static working current of the DSPB can be further optimized, a multi-objective energy consumption optimization model with the floating time and the energy consumption of the oil pump motor as objective functions has been established. The non-dominated sorted genetic algorithm-II (NSGA-II) has been employed to optimized the energy consumption model in the ascent stage of the DSPB. The results showed that the NSGA-II method has a good performance in the energy consumption optimization of the DSPB, and can reduce the dynamic energy consumption in the floating process by 28.9% within 2 h considering the increase in static energy consumption.
机译:为了降低深海自我维持型材浮标(DSPB)的能量消耗并延长其运行时间,本文提出了一种级定量的油排水控制模式。已经研究了系统参数,包括排油液分辨率(ODR),浮动速度的判断阈值和系统能耗的排水频率。通过组合DSPB的浮动运动模型,建立了单观优化模型作为目标函数的总能耗。同时,随着DSPB的静态工作电流可以进一步优化,已经建立了具有浮动时间的多目标能量消耗优化模型和作为客观函数的油泵电机的能量消耗。已经采用非主导的分类遗传算法-II(NSGA-II)在DSPB的上升阶段优化了能量消耗模型。结果表明,NSGA-II方法在DSPB的能量消耗优化方面具有良好的性能,并且考虑到静电能耗的增加,2小时内可以将浮动过程中的动态能耗降低28.9%。

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