Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction

He Ming; Ma Chunyan; Duan Qing; Ni Shan; Deng Wenwen; Liu Xinyan; Li Zhenyi; Chen Yin; Shi Yong

doi:10.1109/EEBDA53927.2022.9744887

Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction

He Ming
, Ma Chunyan
, Duan Qing
, Ni Shan
, Deng Wenwen
, Liu Xinyan
, Li Zhenyi
, Chen Yin
, Shi Yong

State Grid Sichuan Electric Power Company
State Grid Corporation of China
Hefei University of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

8 引用（Scopus）

摘要

Network reconfiguration is an important method to optimize the operation of the active distribution system. It can achieve the goal of reducing network loss and improving power quality by changing the state of network switch without requiring additional equipment investment. The randomness of photovoltaic power generation makes the network reconfiguration of the distribution network need to consider the characteristics of photovoltaic power generation for dynamic optimization. In this paper, a photovoltaic power generation prediction method based on the combination of similar day BP neural network is proposed. The dynamic reconfiguration of distribution network is carried out with the minimum network loss and minimum voltage offset as the objective function, which is optimized by genetic algorithm. Finally, the effectiveness of the proposed model is verified by taking the improved IEEE 33 bus system as an example.

源语言	英语
主期刊名	2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022
出版商	Institute of Electrical and Electronics Engineers Inc.
页	82-87
页数	6
ISBN（电子版）	9781665416061
DOI	https://doi.org/10.1109/EEBDA53927.2022.9744887
出版状态	已出版 - 2022
已对外发布	是
活动	2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 - Changchun, 中国期限: 25 2月 2022 → 27 2月 2022

丛书

姓名	2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022

会议

会议	2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022
国家/地区	中国
市	Changchun
时期	25/02/22 → 27/02/22

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 7 经济适用的清洁能源

访问文件

10.1109/EEBDA53927.2022.9744887

其它文件与链接

链接到 Scopus 的出版物

引用此

Ming, H., Chunyan, M., Qing, D., Shan, N., Wenwen, D., Xinyan, L., Zhenyi, L., Yin, C., & Yong, S. (2022). Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction. 在 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 (页码 82-87). (2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEBDA53927.2022.9744887

Ming, He ; Chunyan, Ma ; Qing, Duan 等. / Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction. 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 82-87 (2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022).

@inproceedings{626b181fbe244a07aee448ea3fbc0f01,

title = "Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction",

abstract = "Network reconfiguration is an important method to optimize the operation of the active distribution system. It can achieve the goal of reducing network loss and improving power quality by changing the state of network switch without requiring additional equipment investment. The randomness of photovoltaic power generation makes the network reconfiguration of the distribution network need to consider the characteristics of photovoltaic power generation for dynamic optimization. In this paper, a photovoltaic power generation prediction method based on the combination of similar day BP neural network is proposed. The dynamic reconfiguration of distribution network is carried out with the minimum network loss and minimum voltage offset as the objective function, which is optimized by genetic algorithm. Finally, the effectiveness of the proposed model is verified by taking the improved IEEE 33 bus system as an example.",

keywords = "Active distribution network, Genetic algorithm, Network reconfiguration, Photovoltaic power generation forecast",

author = "He Ming and Ma Chunyan and Duan Qing and Ni Shan and Deng Wenwen and Liu Xinyan and Li Zhenyi and Chen Yin and Shi Yong",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 ; Conference date: 25-02-2022 Through 27-02-2022",

year = "2022",

doi = "10.1109/EEBDA53927.2022.9744887",

language = "英语",

series = "2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "82--87",

booktitle = "2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022",

}

Ming, H, Chunyan, M, Qing, D, Shan, N, Wenwen, D, Xinyan, L, Zhenyi, L, Yin, C & Yong, S 2022, Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction. 在 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022. 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022, Institute of Electrical and Electronics Engineers Inc., 页码 82-87, 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022, Changchun, 中国, 25/02/22. https://doi.org/10.1109/EEBDA53927.2022.9744887

Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction. / Ming, He; Chunyan, Ma; Qing, Duan 等.
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 82-87 (2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction

AU - Ming, He

AU - Chunyan, Ma

AU - Qing, Duan

AU - Shan, Ni

AU - Wenwen, Deng

AU - Xinyan, Liu

AU - Zhenyi, Li

AU - Yin, Chen

AU - Yong, Shi

PY - 2022

Y1 - 2022

N2 - Network reconfiguration is an important method to optimize the operation of the active distribution system. It can achieve the goal of reducing network loss and improving power quality by changing the state of network switch without requiring additional equipment investment. The randomness of photovoltaic power generation makes the network reconfiguration of the distribution network need to consider the characteristics of photovoltaic power generation for dynamic optimization. In this paper, a photovoltaic power generation prediction method based on the combination of similar day BP neural network is proposed. The dynamic reconfiguration of distribution network is carried out with the minimum network loss and minimum voltage offset as the objective function, which is optimized by genetic algorithm. Finally, the effectiveness of the proposed model is verified by taking the improved IEEE 33 bus system as an example.

AB - Network reconfiguration is an important method to optimize the operation of the active distribution system. It can achieve the goal of reducing network loss and improving power quality by changing the state of network switch without requiring additional equipment investment. The randomness of photovoltaic power generation makes the network reconfiguration of the distribution network need to consider the characteristics of photovoltaic power generation for dynamic optimization. In this paper, a photovoltaic power generation prediction method based on the combination of similar day BP neural network is proposed. The dynamic reconfiguration of distribution network is carried out with the minimum network loss and minimum voltage offset as the objective function, which is optimized by genetic algorithm. Finally, the effectiveness of the proposed model is verified by taking the improved IEEE 33 bus system as an example.

KW - Active distribution network

KW - Genetic algorithm

KW - Network reconfiguration

KW - Photovoltaic power generation forecast

UR - https://www.scopus.com/pages/publications/85128664766

U2 - 10.1109/EEBDA53927.2022.9744887

DO - 10.1109/EEBDA53927.2022.9744887

M3 - 会议稿件

AN - SCOPUS:85128664766

T3 - 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022

SP - 82

EP - 87

BT - 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022

Y2 - 25 February 2022 through 27 February 2022

ER -

Ming H, Chunyan M, Qing D, Shan N, Wenwen D, Xinyan L 等. Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction. 在 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022. Institute of Electrical and Electronics Engineers Inc. 2022. 页码 82-87. (2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022). doi: 10.1109/EEBDA53927.2022.9744887

Active Distribution Network Reconfiguration Method Based on Photovoltaic Generation Prediction

摘要

丛书

会议

联合国可持续发展目标

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