Maximum efficiency point tracking for an ocean thermal energy harvesting system,International Journal of Energy Research

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Maximum efficiency point tracking for an ocean thermal energy harvesting system
International Journal of Energy Research ( IF 4.3 ) Pub Date : 2020-01-20 , DOI: 10.1002/er.5055
Qingchao Xia _{1,

2} , Yanhu Chen ₁ , Canjun Yang _{1,

2} , Bingzhe Chen ₁ , Gul Muhammad ₁ , Xiaoxia Ma ₁

Affiliation

Limited energy is the most critical factor that restricts the persistent presence of underwater vehicles in the oceans; thus, harvesting the ocean's thermal energy that is stored in the water column between the sea surface and deep water is a particularly promising solution for the current power shortage. This paper has designed a new ocean thermal energy conversion system which using phase change material as energy storage medium, and proposed a novel maximum efficiency point tracking (MEPT) method for energy conversion. This new method, which is integrated with a radial basis function neural network (RBFNN), particle swarm optimization (PSO) and the proportion integration differentiation (PID) control method, could effectively improve the efficiency of energy conversion. Compared with the power generation system that does not use the MEPT method, experimental results show that the proposed method can improve the efficiency of the power generation from less than 19.05% to more than 34.3% and has higher stability (using this method: the efficiency changes from 34.3%‐34.7%; without using this method: the efficiency changes from 13.56% ‐19.05%) when the load changes. This novel method can be used in many conditions, especially when the mathematical model of the generation system is unknown or researchers want to use fewer sensors for maximum efficiency point tracking.

中文翻译：

海洋热能收集系统的最大效率点跟踪

有限的能源是限制水下航行器在海洋中持续存在的最关键因素。因此，对于当前的电力短缺，收集存储在海面和深水之间的水柱中的海洋热能是一种特别有希望的解决方案。本文设计了一种新的以相变材料为储能介质的海洋热能转化系统，并提出了一种新的最大效率点跟踪（MEPT）能量转化方法。该新方法结合了径向基函数神经网络（RBFNN），粒子群优化（PSO）和比例积分微分（PID）控制方法，可以有效地提高能量转换效率。与不使用MEPT方法的发电系统相比，实验结果表明，该方法可以将发电效率从不到19.05％提高到34.3％以上，并且具有更高的稳定性（使用这种方法：从34.3％-34.7％更改；不使用此方法：负载变化时，效率从13.56％-19.05％更改。这种新颖的方法可以在许多情况下使用，特别是在发电系统的数学模型未知或研究人员希望使用较少的传感器进行最大效率点跟踪时。不使用此方法：负载变化时，效率从13.56％-19.05％改变。这种新颖的方法可以在许多情况下使用，特别是在发电系统的数学模型未知或研究人员希望使用较少的传感器进行最大效率点跟踪时。不使用此方法：负载变化时，效率从13.56％-19.05％改变。这种新颖的方法可以在许多情况下使用，特别是在发电系统的数学模型未知或研究人员希望使用较少的传感器进行最大效率点跟踪时。

更新日期：2020-01-20

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