MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm
Due to the fact that thermoelectric generation (TEG) system commonly operates in environment where temperature distribution is non-uniform, consequently the output characteristic curve P–V for centralized TEG systems gives rise to several local maximum power points (LMPP). The paper suggests a COOT...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X24000996 |
| _version_ | 1827351260235300864 |
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| author | Xiao-Hong Yuan Bo Li Xun Liu Xin Xiong Yi-Ping Wang |
| author_facet | Xiao-Hong Yuan Bo Li Xun Liu Xin Xiong Yi-Ping Wang |
| author_sort | Xiao-Hong Yuan |
| collection | DOAJ |
| description | Due to the fact that thermoelectric generation (TEG) system commonly operates in environment where temperature distribution is non-uniform, consequently the output characteristic curve P–V for centralized TEG systems gives rise to several local maximum power points (LMPP). The paper suggests a COOT algorithm-based maximum power point tracking (MPPT) method for centralized TEG system, by imitating the collective behavior of Coot water birds, which involves their leadership structures and chain movements, to enhance its capability of jumping out the local optima. Furthermore, it integrates a dynamic reverse learning strategy and a dynamic termination condition, which shortens the iteration times and convergence time of the algorithm. To evaluate its performance, this paper conducted distinct case studies that included engine speed at 1000, 2500, and 4000 rpm, step changes and randomly changes. The effectiveness of the COOT algorithm is evaluated by comparing its performance with that of the traditional Perturbation and Observation (P&O) algorithm as well as the meta-heuristic algorithms Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). It is shown that the COOT algorithm can achieve optimum power output and effectively reduce fluctuations in output power, while converging to the optimal solution more quickly. |
| first_indexed | 2024-03-08T02:00:36Z |
| format | Article |
| id | doaj.art-34cc6893053c4587aa8e5cfa6e234cde |
| institution | Directory Open Access Journal |
| issn | 2214-157X |
| language | English |
| last_indexed | 2024-03-08T02:00:36Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj.art-34cc6893053c4587aa8e5cfa6e234cde2024-02-14T05:17:14ZengElsevierCase Studies in Thermal Engineering2214-157X2024-02-0154104068MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithmXiao-Hong Yuan0Bo Li1Xun Liu2Xin Xiong3Yi-Ping Wang4Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China; Hubei Collaborative Innovation Centre for Automotive Components Technology, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China; Hubei Collaborative Innovation Centre for Automotive Components Technology, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China; Hubei Collaborative Innovation Centre for Automotive Components Technology, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China; Hubei Collaborative Innovation Centre for Automotive Components Technology, Wuhan University of Technology, Wuhan, ChinaHubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China; Hubei Collaborative Innovation Centre for Automotive Components Technology, Wuhan University of Technology, Wuhan, China; Corresponding author. Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China.Due to the fact that thermoelectric generation (TEG) system commonly operates in environment where temperature distribution is non-uniform, consequently the output characteristic curve P–V for centralized TEG systems gives rise to several local maximum power points (LMPP). The paper suggests a COOT algorithm-based maximum power point tracking (MPPT) method for centralized TEG system, by imitating the collective behavior of Coot water birds, which involves their leadership structures and chain movements, to enhance its capability of jumping out the local optima. Furthermore, it integrates a dynamic reverse learning strategy and a dynamic termination condition, which shortens the iteration times and convergence time of the algorithm. To evaluate its performance, this paper conducted distinct case studies that included engine speed at 1000, 2500, and 4000 rpm, step changes and randomly changes. The effectiveness of the COOT algorithm is evaluated by comparing its performance with that of the traditional Perturbation and Observation (P&O) algorithm as well as the meta-heuristic algorithms Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). It is shown that the COOT algorithm can achieve optimum power output and effectively reduce fluctuations in output power, while converging to the optimal solution more quickly.http://www.sciencedirect.com/science/article/pii/S2214157X24000996Centralized thermoelectric generation systemMaximum power pointCOOT algorithm optimizationNon-uniform temperature distributions |
| spellingShingle | Xiao-Hong Yuan Bo Li Xun Liu Xin Xiong Yi-Ping Wang MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm Case Studies in Thermal Engineering Centralized thermoelectric generation system Maximum power point COOT algorithm optimization Non-uniform temperature distributions |
| title | MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm |
| title_full | MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm |
| title_fullStr | MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm |
| title_full_unstemmed | MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm |
| title_short | MPPT design of centralized thermoelectric generation system under non-uniform temperature distribution based on COOT optimization algorithm |
| title_sort | mppt design of centralized thermoelectric generation system under non uniform temperature distribution based on coot optimization algorithm |
| topic | Centralized thermoelectric generation system Maximum power point COOT algorithm optimization Non-uniform temperature distributions |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X24000996 |
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