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Coordinated optimization scheduling technology for multiregion virtual power plants based on improved Grey Wolf Optimization Algorithm
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Guanquan Dai1, Kaiyan Pan2, Ying Cai1, Guobiao Lin2, Shunqi Zeng1, Yuxiang Huang3, Xiaojie Liu2
Renewable Energy Resources | 2024, 42(12) : 1681 - 1688
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Renewable Energy Resources | 2024, 42(12): 1681-1688
Coordinated optimization scheduling technology for multiregion virtual power plants based on improved Grey Wolf Optimization Algorithm
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Guanquan Dai1, Kaiyan Pan2, Ying Cai1, Guobiao Lin2, Shunqi Zeng1, Yuxiang Huang3, Xiaojie Liu2
Affiliations
  • 1 Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd. Guangzhou 518000 China
  • 2 Dongfang Electronics Co., Ltd. Yantai 264000 China
  • 3 South China University of Technology Guangzhou 510641 China
Published: 2024-12-20
Outline
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To promote the realization of the "dual carbon" goal, the distributed new energy in different regions of the virtual power plant is coordinated and optimized through lowcarbon power generation. A multi region virtual power plant coordinated and optimized scheduling technology based on the Grey Wolf Optimization Algorithm is proposed. Firstly, construct an operational optimization model with the best economic benefits, connecting virtual power plants in different regions with distributed new energy, and jointly scheduling wind and solar power generation units and carbon capture units; Secondly, due to the difficulty in solving, strong nonlinearity, and high dimensionality of the constructed model, the advantages of the Grey Wolf Optimization Algorithm such as high search efficiency, fast convergence speed, and few optimization parameters are utilized to optimize the model. At the same time, an improved Grey Wolf Optimization Algorithm is proposed to improve the algorithm's global optimization ability and solve the problem of premature and local optima in the later stage of the algorithm; Finally, through simulation verification, the proposed method can achieve optimal scheduling of virtual power plants in different regions, reducing carbon emissions and net costs.

low carbon electricity  /  virtual power plant  /  distributed new energy  /  Grey Wolf Optimization Algorithm  /  optimize scheduling
Guanquan Dai, Kaiyan Pan, Ying Cai, Guobiao Lin, Shunqi Zeng, Yuxiang Huang, Xiaojie Liu. Coordinated optimization scheduling technology for multiregion virtual power plants based on improved Grey Wolf Optimization Algorithm[J]. Renewable Energy Resources, 2024 , 42 (12) : 1681 -1688 .
Year 2024 volume 42 Issue 12
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Article Info
  • Receive Date:2023-11-24
  • Online Date:2025-07-22
  • Published:2024-12-20
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  • Received:2023-11-24
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    1 Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd. Guangzhou 518000 China
    2 Dongfang Electronics Co., Ltd. Yantai 264000 China
    3 South China University of Technology Guangzhou 510641 China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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