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Large-scale unit combination optimization method for multi-stack fuel cell power generation system

A fuel cell stack, fuel cell technology, applied in electrical components, circuit devices, AC network circuits, etc., can solve problems such as inability to improve fuel cell life, reduce costs, etc., to improve adaptability and stability, and improve economy. performance, prolonging working life

Active Publication Date: 2018-09-04
SOUTHWEST JIAOTONG UNIV
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Problems solved by technology

[0004] At present, there are relatively few studies on fuel cell power generation arrays at home and abroad, and there is no relatively detailed explanation and explanation for the control of multi-stack large-scale unit output, which cannot improve the short life of fuel cells and reduce costs.

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  • Large-scale unit combination optimization method for multi-stack fuel cell power generation system
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  • Large-scale unit combination optimization method for multi-stack fuel cell power generation system

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Embodiment Construction

[0056] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described with reference to the accompanying drawings.

[0057] In this embodiment, see figure 1 As shown, the present invention proposes a large-scale unit combination optimization method for a multi-stack fuel cell power generation system, which includes the steps:

[0058] In step S100, the fuel cell stack is clustered according to the scene by K-means clustering method and Monte Carlo simulation method and a probability distribution model is established;

[0059] Step S200, using an adaptive inertia weighting algorithm to make each fuel cell stack search and follow the current optimal solution in the solution space according to the probability distribution model, so as to achieve optimal distribution of the output power of each fuel cell stack.

[0060] Based on the optimization solution of the foregoing embodiment, step S100 includes ...

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Abstract

The invention discloses a large-scale unit combination optimization method for a multi-stack fuel cell power generation system, which comprises the steps of clustering fuel cell stacks according to the scene through a K-means clustering method and a Monte Carlo simulation method, and building a probability distribution model; enabling each fuel cell stack to search and follow the current optimal solution in a solution space according to the probability distribution model by applying an adaptive inertia weight algorithm, and achieving the optimal distribution of the output power of each fuel cell stack. According to the invention, the reasonable output of large-scale units of a fuel cell power generation array system is ensured, the on-off of each stack and the shifting between the stacks are controlled through the adaptive inertia weight algorithm, so that the service life of fuel cells is prolonged, the system stability is improved, the system cost is reduced, and a purpose of fuel economy is achieved.

Description

Technical field [0001] The invention belongs to the technical field of fuel cells, and particularly relates to a method for optimizing large-scale unit combination of a multi-stack fuel cell power generation system. Background technique [0002] The energy problem is now a serious problem that cannot be ignored. Traditional fossil energy is declining or even exhausted, and it can no longer meet the daily needs of mankind. As a result, more and more new high-quality energy sources are emerging. At the same time, it is necessary to master and use advanced energy technology. The development and utilization of new, clean and renewable energy is imperative. Fuel cell is a clean and high-efficiency power generation device. As an important part of distributed power generation, fuel cell has attracted wide attention for its many advantages. In particular, the proton exchange membrane fuel cell (PEMFC) has the characteristics of low operating temperature, low noise, high efficiency, and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06H02J3/46H02J3/38
CPCG06Q10/04G06Q10/06312G06Q50/06H02J3/387H02J3/46H02J2203/20
Inventor 陈维荣朱亚男李奇黄文强邓惠文尚伟林苏波
Owner SOUTHWEST JIAOTONG UNIV
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