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Research on optimization strategies for the operation of multiple transformer districts con-sidering the uncertainty of distributed renewable energy output and carbon emission costs
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Jianbo Wang1, Zekai Qiu1, Xiaoqing Zhang1, Minna Dou1, Xiao Liu2, Yufan Lu2, Xilin Lü1, Lirong Wang1
Renewable Energy Resources | 2024, 42(3) : 407 - 419
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Renewable Energy Resources | 2024, 42(3): 407-419
Research on optimization strategies for the operation of multiple transformer districts con-sidering the uncertainty of distributed renewable energy output and carbon emission costs
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Jianbo Wang1, Zekai Qiu1, Xiaoqing Zhang1, Minna Dou1, Xiao Liu2, Yufan Lu2, Xilin Lü1, Lirong Wang1
Affiliations
  • 1 Power Research Institute State Grid Shaanxi Electric Power Co., LTD. Xi'an 710100 China
  • 2 North China Electric Power University Beijing 102206 China
Published: 2024-03-20 doi: https://doi.org/10.16081/j.epae.202305007
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With the marketoriented reform of power grid companies, the power market will gradually attract the investment of various social capital. The transformer districts (TDs) subordinated to the distribution network and the distribution network itself provided a platform for the multiagent competition, forming a competitive game pattern. At the same time, the high proportion of DRE access improves the cleanliness of the distribution network, but the uncertainty of DREs' output also leads to the further increase of the distribution network dispatching operation risk.To mitigate the uncertainty, the distributed renewable energy, distributed thermal power generation, energy storage and flexible load within the same TD is treated as a whole and regulated by the distribution grid operator with the objectives of safety and economy. Firstly, a leader follower game model consists of the distribution grid operator and multiple transformer districts is established to coordinate the interests between the distribution grid operator and its subordinate TDs. Conditional valueatrisk theory is used to quantify the uncertainty risk caused by renewable energy represented by wind and solar power. Next, the profit of each TD in the carbon market is incorporated into the optimization scheduling model to further consider the carbon emission costs of distributed thermal power generation achieving flexible complementary regulation between distributed renewable energy and thermal power. The BP neural network is used to fit the model, simplifying the leaderfollower game model into a singlelevel model, which is then solved using a particle swarm algorithm. Finally, the variations in distributed power generation within each TD under different renewable energy output risks and carbon prices are discussed to further validate the effectiveness of the model.

uncertainty  /  carbon emission costs  /  conditional value-at-risk  /  BP neural network  /  stackelberg game
Jianbo Wang, Zekai Qiu, Xiaoqing Zhang, Minna Dou, Xiao Liu, Yufan Lu, Xilin Lü, Lirong Wang. Research on optimization strategies for the operation of multiple transformer districts con-sidering the uncertainty of distributed renewable energy output and carbon emission costs[J]. Renewable Energy Resources, 2024 , 42 (3) : 407 -419 . DOI: https://doi.org/10.16081/j.epae.202305007
Year 2024 volume 42 Issue 3
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doi: https://doi.org/10.16081/j.epae.202305007
  • Receive Date:2023-10-17
  • Online Date:2025-07-22
  • Published:2024-03-20
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  • Received:2023-10-17
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    1 Power Research Institute State Grid Shaanxi Electric Power Co., LTD. Xi'an 710100 China
    2 North China Electric Power University Beijing 102206 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
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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