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

Mingcong Liu, Shaobo Yang, Hongyu Li, Jiayi Xu and Xingfei Li
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Mingcong Liu: State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
Shaobo Yang: State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
Hongyu Li: Shandong University of Science and Technology, Qingdao 266590, China
Jiayi Xu: State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
Xingfei Li: State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China

Energies, 2019, vol. 12, issue 12, 1-26

Abstract: 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.

Keywords: energy consumption optimization; deep-sea self-sustaining profile buoy (DSPB); multi-objective optimization; non-dominated sorted genetic algorithm-II (NSGA-II) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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