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Citation:Bo Yang,Jinhang Duan,Yunfeng Yan,et al.EMCO-based optimal layout design of hybrid wind-wave energy converters array[J].Protection and Control of Modern Power Systems,2024,V9(5):142-161[Copy]
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EMCO-based optimal layout design of hybrid wind-wave energy converters array
Bo Yang,Jinhang Duan,Yunfeng Yan,Bingqiang Liu,Jianxiang Huang,Lin Jiang,Rui Han
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Abstract:
Marine renewable energy, combining wave energy converters (WECs) and floating wind turbines (FWTs) into hybrid wave-wind energy converters (HWWECs), garners significant global interest. HWWECs offer potential cost reductions, increased power generation, and enhanced system stability. The absorption power of high wind energy sites is primarily influenced by the complex hydrodynamic interactions among floating bodies, which are closely related to the location and wind-wave environment of high wind energy sites. To delve into the positive interactions among HWWECs, this paper proposes a HWWEC array optimization strategy based on the artificial ecosystem optimization-manta ray foraging optimization coordinated optimizer (EMCO). In EMCO, the decomposition operator of artificial ecosystem optimization (AEO) and the flipping-dipper foraging operator of manta ray foraging optimization coordinated (MRFO) cooperate dynamically to effectively balance local exploitation and global exploration. To validate the effectiveness of EMCO, experiments were conducted in scenarios with 3, 5, 8, and 20 HWWECs, and compared with five typical algorithms. Experimental results demonstrate the existence of multiple optimal solutions for HWWEC arrays. EMCO achieves maximum total absorption power and exhibits good stability. Notably, EMCO enhances the q -factor values of HWWECs across four scales: 1.0478, 1.0586, 1.0612, and 0.9965, respectively.
Key words:  Marine renewable energy, hybrid wind-wave energy converter, layout optimization, coordinating optimizer.
DOI:10.23919/PCMP.2023.000129
Fund:This work is supported by the National Natural Science Foundation of China (No. 61963020 and No. 62263014) and Yunnan Provincial Basic Research Project (No. 202201AT070857).
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