| 引用本文: | 马 遵,和 鹏,许珂玮,等.基于混沌博弈优化的固体氧化物燃料电池模型参数优化设计[J].电力系统保护与控制,2024,52(6):15-28. |
| MA Zun,HE Peng,XU Kewei,et al.Optimal parameter design of models for SOFCs using chaos game optimization[J].Power System Protection and Control,2024,52(6):15-28 |
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| 摘要: |
| 固体氧化物燃料电池(solid oxide fuel cell, SOFC)因具有转换效率高、无污染物排放、运行噪声低等特点被视为前景广阔的绿色发电技术之一，其被广泛应用于电力系统和交通运输等领域。针对SOFC稳态模型的参数优化设计问题，提出了一种基于混沌博弈优化(chaos game optimization, CGO)方法的SOFCs参数提取框架。同时，利用芬兰燃料电池技术公司Elcogen生产的陶瓷阳极支撑型平板式低温单体燃料电池(ASC-400B)工作于两种不同温度(即600 ℃和700 ℃)下的实验数据以及美国蒙大拿州立大学开发的基于物理模型的5 kW级管式SOFC电池堆栈模型在两种不同温度(即850 ℃和950 ℃)下的仿真数据，分别对所提框架、蒲公英优化器(dandelion optimizer, DO)、平衡优化器(equilibrium optimizer, EO)、粒子群优化(particle swarm optimization, PSO)算法和白鲨优化器(white shark optimizer, WSO)的参数提取的性能进行了深入的研究和分析。测试结果表明：相比于DO、EO、PSO和WSO，CGO能够准确、稳定且快速地提取上述各种SOFCs的模型未知参数，为SOFCs的系统建模提供了一种高效的方法。 |
| 关键词: 参数设计 固体氧化物燃料电池 系统建模 混沌博弈优化 元启发式算法 |
| DOI：10.19783/j.cnki.pspc.230635 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(62263014) |
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| Optimal parameter design of models for SOFCs using chaos game optimization |
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MA Zun1, HE Peng1, XU Kewei1, MENG Xian1, HE Tingyi1, YANG Bo2
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1. Yunnan Power Grid Co., Ltd. Research Institute, Kunming 650000, China; 2. School of Electric Power Engineering,
Kunming University of Science and Technology, Kunming 650500, China
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| Abstract: |
| The solid oxide fuel cell (SOFC) is regarded as one of the most promising green power generation technologies because of its characteristics of high conversion efficiency, no pollutant emission and low operating noise. It is widely used in power systems, transportation and other fields. This paper proposes a parameter extraction framework for SOFCs based on the chaos game optimization (CGO) method, which addresses the parameter optimization design problem of SOFC steady-state models. In-depth research and analysis have been conducted on the performance of parameter extraction using the proposed framework, the dandelion optimizer (DO), the equilibrium optimizer (EO), the particle swarm optimization (PSO) algorithm, and the white shark optimizer (WSO) for experimental data of ceramic anode-supported planar low-temperature single-cell fuel cells (ASC-400B) produced by the Finnish fuel cell technology company Elcogen operating at two different temperatures (i.e., 600 ℃ and 700 ℃), as well as simulation data from a 5 kW-level tubular SOFC stack model developed based on physical models by Montana State University, also at two different temperatures (i.e., 850 ℃ and 950 ℃). The test results indicate that compared to DO, EO, PSO, and WSO, CGO can accurately, stably, and rapidly extract the model unknown parameters of various SOFCs mentioned above, providing an efficient method for system modeling of SOFCs. |
| Key words: parameter design solid oxide fuel cell system modeling chaos game optimization meta-heuristics algorithm |
