中国电力 ›› 2018, Vol. 51 ›› Issue (8): 77-84.DOI: 10.11930/j.issn.1004-9649.201805160

• 能源互联网关键技术及应用专栏 • 上一篇    下一篇

考虑共享储能的社区综合能源系统协同优化研究

王仕俊, 平常, 薛国斌   

  1. 国网甘肃省电力公司经济技术研究院, 甘肃 兰州 730050
  • 收稿日期:2018-05-23 修回日期:2018-07-13 出版日期:2018-08-05 发布日期:2018-11-01
  • 作者简介:王仕俊(1988-),男,硕士,工程师,从事电力系统规划及电网建设管理工作,综合能源系统优化研究,E-mail:wangshijun_1988@163.com;平常(1988-),男,硕士,工程师,从事电力通信规划及项目管理工作,E-mail:519501410@qq.com;薛国斌(1978-),男,硕士,高级工程师,从事电力系统规划及电网建设管理工作,E-mail:10609548@qq.com
  • 基金资助:
    国网甘肃省电力公司科技项目(52272817000X);甘肃省青年科技基金资助项目。

Synergic Optimization of Community Energy Internet Considering the Shared Energy Storage

WANG Shijun, PING Chang, XUE Guobin   

  1. State Grid Economy & Technology Research Institute of Gansu Province Electric Power Corporation, Lanzhou 730050, China
  • Received:2018-05-23 Revised:2018-07-13 Online:2018-08-05 Published:2018-11-01
  • Supported by:
    This work is supported by Science and Technology Project of State Grid Gansu Electric Power Corporation (No.52272817000X),Youth Science and Technology Funding Scheme of Gansu Province (No.17JR5RA346).

摘要: 以综合能源系统为核心的能源互联网是解决能源危机和环境污染问题的一个重要途径。以社区综合能源系统为研究对象,提出了包含共享储能、热电联供以及光伏电源等设备的用户协同优化模型。首先,建立社区综合能源系统中重要设备及负荷的模型;其次,分别建立用户电网购电费用、社区运行商购能费用、储能系统租赁费用等模型,并以此建立以用户整体经济性最优作为目标的协同优化模型;再次,基于用户日能耗量对整体费用进行合理再分配;最后,利用具体算例对所提模型进行有效性分析。算例结果表明,所提方案有助于用户合理优化用能安排,从而降低用能费用。

关键词: 社区综合能源系统, 社区运行商, 协同优化, 共享储能, 改进PSO

Abstract: The energy internet, which takes the integrated energy system as the core, is an important way to solve the energy crisis and environmental pollution problems. Taking the community energy internet as the research object, this paper proposes a synergic optimization model containing shared energy storage, CHP, and PV generation. Firstly, models are built for the important equipment and power load in the integrated energy internet; and then, different models are built respectively for the electricity purchase cost from the power grid, the energy purchase cost from community micro operator, and the leasing cost from storage system, and accordingly, a synergic optimization model is founded aiming at the global economic optimization of the users; furthermore, the coalition cost is divided among users based on the daily energy consumption amount; lastly, a case study is conducted to verify the effectiveness of the proposed method. The simulation result shows that the proposed approach can schedule energy consumption reasonably to reduce the energy cost of users.

Key words: community integrated energy system, community operator, synergic optimization, shared energy storage, improved PSO

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