Hybrid AC/DC Microgrid Energy Management Based on Renewable Energy Sources Forecasting

被引：0

作者：

Yuan, Baolei ^{[1
]}

Chen, Alian ^{[1
]}

Du, Chunshui ^{[1
]}

Zhang, Chenghui ^{[1
]}

机构：

[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Shandong, Peoples R China

来源：

PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年

基金：

中国国家自然科学基金;

关键词：

Hybrid AC/DC microgrid; Renewable energy sources forecasting; Energy management;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Energy management is the core of economical and efficient operation for hybrid AC/DC microgrid. In this paper, renewable energy sources are forecast by using BP neural network based on modified particle swarm optimization (MPSO-BP). Compared with traditional algorithm, the modified algorithm performs better in both search ability and speed. After forecasting, with the objectives of minimum total cost and minimum power loss, the optimal model is built. The output is optimized through coordinating all kinds of DGs. The simulation results verified the effectiveness of the proposed model in multi-objective optimization of hybrid microgrid. Through the energy management dispatch, the hybrid microgrid could realize the optimized operation level.

引用

页码：2870 / 2875

页数：6

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