系统仿真学报 ›› 2023, Vol. 35 ›› Issue (5): 1075-1085.doi: 10.16182/j.issn1004731x.joss.22-0072

• 论文 • 上一篇    下一篇

基于新型BBO算法的微电网优化调度研究

魏利胜1,2(), 杨奔奔1,2, 孙瑞霞2   

  1. 1.安徽省电气传动与控制重点实验室,安徽 芜湖 241000
    2.安徽工程大学 电气工程学院,安徽 芜湖 241000
  • 收稿日期:2022-01-23 修回日期:2022-03-21 出版日期:2023-05-30 发布日期:2023-05-22
  • 作者简介:魏利胜(1978-),男,教授,博士,研究方向为图像识别与应用、智能信息处理及应用。E-mail:lshwei_11@163.com
  • 基金资助:
    安徽省教育厅重大项目(KJ2020ZD39)

Research on Optimal Scheduling of Microgrid Based on NBBO Algorithm

Lisheng Wei1,2(), Benben Yang1,2, Ruixia Sun2   

  1. 1.Anhui Key Laboratory of Electric Drive and Control, Wuhu 241000, China
    2.School of Electrical Engineering, Anhui Polytechnic University, Wuhu 241000, China
  • Received:2022-01-23 Revised:2022-03-21 Online:2023-05-30 Published:2023-05-22

摘要:

针对含微型燃气轮机的微电网经济性与环保性协同优化问题,引入具有弃风弃光消纳和碳捕获能力的电转气(pow to gas, P2G)系统,提出了一种基于新型生物地理学优化算法(novel biogeography-based optimization, NBBO)的含P2G系统的微电网优化调度模型。构建含P2G系统的微电网模型,并分析主要设备的工作原理;引入风机备用容量以降低风力发电随机性的影响;建立微电网运行成本最小的目标函数,运用提出的NBBO算法求解该目标函数。通过分析可知,含P2G系统的微电网可减少9.02%的发电成本,降低25.9%的含碳氧化物排放,验证了所提含P2G系统的微电网模型的可行性及改进算法的适用性和优越性。

关键词: 微电网, 生物地理学优化算法, 电转气, 低碳化, 策略研究

Abstract:

In view of the economic and environmental collaborative optimization of a microgrid with a micro gas turbine, power to gas(P2G) system with the ability to abandon wind and light for consumption and capture carbon is introduced, and a microgrid optimal scheduling model with P2G system based on novel biogeography-based optimization(NBBO) algorithm is proposed. The microgrid model with the P2G system is constructed, and the working principle of the main equipment is analyzed. The reserve capacity of a wind turbine is introduced to reduce the influence of the randomness of wind power generation. The objective function of minimizing the operating cost of the microgrid is established, and the proposed NBBO algorithm is used to solve the objective function. The analysis shows that the microgrid with a P2G system can reduce the power generation cost by 9.02% and the emission of carbon oxides by 25.9%, which verifies the feasibility of the proposed microgrid model with P2G system and the applicability and superiority of the improved algorithm.

Key words: microgrid, biogeography-based optimization algorithm, power to gas, low-carbon, strategy research

中图分类号: