A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network

Hongyan Pei; Yunhua Li; Keyan Liu

doi:10.1109/CGNCC.2016.7828905

A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network

Hongyan Pei
, Yunhua Li^*
, Keyan Liu

^*此作品的通讯作者

自动化科学与电气工程学院

Beihang University
Electric Power Research Institute of China

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

4 引用（Scopus）

摘要

Heuristic search algorithms, based on their advantages in multi-objective and multi-dimensions optimization, have been widely utilized in reactive power optimization problem. In this paper, we propose a new heuristic search algorithm, named black hole gravitational search algorithm (BHGSA), which is combined black hole algorithm (BHA) with gravitational search algorithm (GSA), to solve day-ahead reactive power optimization problem in distribution network. The simulation result to solve the day-ahead reactive power optimization problem of IEEE 33-bus distribution network system with wind generators and photovoltaic generator using BHGSA is provided. By compared with traditional gravitational search algorithm, it presents advantages in global searching ability and avoiding early convergence.

源语言	英语
主期刊名	CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
出版商	Institute of Electrical and Electronics Engineers Inc.
页	901-906
页数	6
ISBN（电子版）	9781467383189
DOI	https://doi.org/10.1109/CGNCC.2016.7828905
出版状态	已出版 - 20 1月 2017
活动	7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, 中国期限: 12 8月 2016 → 14 8月 2016

出版系列

姓名	CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

会议

会议	7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
国家/地区	中国
市	Nanjing, Jiangsu
时期	12/08/16 → 14/08/16

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/CGNCC.2016.7828905

其它文件与链接

链接到 Scopus 的出版物

引用此

Pei, H., Li, Y., & Liu, K. (2017). A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network. 在 CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference (页码 901-906). 文章 7828905 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CGNCC.2016.7828905

Pei, Hongyan ; Li, Yunhua ; Liu, Keyan. / A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network. CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc., 2017. 页码 901-906 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference).

@inproceedings{6795d5d19a2548b785a8e2e7923fd09a,

title = "A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network",

abstract = "Heuristic search algorithms, based on their advantages in multi-objective and multi-dimensions optimization, have been widely utilized in reactive power optimization problem. In this paper, we propose a new heuristic search algorithm, named black hole gravitational search algorithm (BHGSA), which is combined black hole algorithm (BHA) with gravitational search algorithm (GSA), to solve day-ahead reactive power optimization problem in distribution network. The simulation result to solve the day-ahead reactive power optimization problem of IEEE 33-bus distribution network system with wind generators and photovoltaic generator using BHGSA is provided. By compared with traditional gravitational search algorithm, it presents advantages in global searching ability and avoiding early convergence.",

author = "Hongyan Pei and Yunhua Li and Keyan Liu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 ; Conference date: 12-08-2016 Through 14-08-2016",

year = "2017",

month = jan,

day = "20",

doi = "10.1109/CGNCC.2016.7828905",

language = "英语",

series = "CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference",

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

pages = "901--906",

booktitle = "CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference",

address = "美国",

}

Pei, H, Li, Y & Liu, K 2017, A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network. 在 CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference., 7828905, CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference, Institute of Electrical and Electronics Engineers Inc., 页码 901-906, 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016, Nanjing, Jiangsu, 中国, 12/08/16. https://doi.org/10.1109/CGNCC.2016.7828905

A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network. / Pei, Hongyan; Li, Yunhua; Liu, Keyan.
CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc., 2017. 页码 901-906 7828905 (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network

AU - Pei, Hongyan

AU - Li, Yunhua

AU - Liu, Keyan

PY - 2017/1/20

Y1 - 2017/1/20

N2 - Heuristic search algorithms, based on their advantages in multi-objective and multi-dimensions optimization, have been widely utilized in reactive power optimization problem. In this paper, we propose a new heuristic search algorithm, named black hole gravitational search algorithm (BHGSA), which is combined black hole algorithm (BHA) with gravitational search algorithm (GSA), to solve day-ahead reactive power optimization problem in distribution network. The simulation result to solve the day-ahead reactive power optimization problem of IEEE 33-bus distribution network system with wind generators and photovoltaic generator using BHGSA is provided. By compared with traditional gravitational search algorithm, it presents advantages in global searching ability and avoiding early convergence.

AB - Heuristic search algorithms, based on their advantages in multi-objective and multi-dimensions optimization, have been widely utilized in reactive power optimization problem. In this paper, we propose a new heuristic search algorithm, named black hole gravitational search algorithm (BHGSA), which is combined black hole algorithm (BHA) with gravitational search algorithm (GSA), to solve day-ahead reactive power optimization problem in distribution network. The simulation result to solve the day-ahead reactive power optimization problem of IEEE 33-bus distribution network system with wind generators and photovoltaic generator using BHGSA is provided. By compared with traditional gravitational search algorithm, it presents advantages in global searching ability and avoiding early convergence.

UR - https://www.scopus.com/pages/publications/85015167890

U2 - 10.1109/CGNCC.2016.7828905

DO - 10.1109/CGNCC.2016.7828905

M3 - 会议稿件

AN - SCOPUS:85015167890

T3 - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

SP - 901

EP - 906

BT - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016

Y2 - 12 August 2016 through 14 August 2016

ER -

Pei H, Li Y, Liu K. A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network. 在 CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference. Institute of Electrical and Electronics Engineers Inc. 2017. 页码 901-906. 7828905. (CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference). doi: 10.1109/CGNCC.2016.7828905

A multi-object black hole gravitational search algorithm for day-ahead reactive optimization in distribution network

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

学术指纹

引用此