发电技术 ›› 2019, Vol. 40 ›› Issue (5): 440-447.DOI: 10.12096/j.2096-4528.pgt.19081

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极端灾害下基于智能楼宇分布式电源的配电系统负荷恢复力评估分析

方伟(),曾博*(),徐富强,张建华   

  • 收稿日期:2019-05-20 出版日期:2019-10-30 发布日期:2019-11-05
  • 通讯作者: 曾博
  • 作者简介:方伟(1992),男,硕士研究生,研究方向为综合能源系统规划与运行, ncepufangwei@ncepu.edu.cn
  • 基金资助:
    中央高校基本科研专项资金(2017MS007)

Evaluation on Load Restoration of Distribution System Based on Distributed Generation in Smart Buildings After Extreme Disasters

Wei FANG(),Bo ZENG*(),Fuqiang XU,Jianhua ZHANG   

  • Received:2019-05-20 Published:2019-10-30 Online:2019-11-05
  • Contact: Bo ZENG
  • Supported by:
    Fundamental Research Funds for the Central Universities(2017MS007)

摘要:

作为一类重要的负荷侧资源,智能楼宇中广泛存在的各类分布式电源为极端灾害后电力系统的供电快速恢复及负荷转带提供了新的可能性。为此,提出一种针对智能楼宇负荷恢复力的综合评估框架,用于定量分析和计算极端灾害后智能楼宇末端存活分布式电源对配电系统中重要负荷的转带能力。在对智能楼宇内不同类型物理设备进行建模的基础上,重点考虑多能互补及能量耦合特性,首先,提出了电能转移量、热能转移量、冷能转移量3项定量评价指标,用于精确量化极端灾害后智能楼宇电源对系统负荷恢复的贡献。其次,在此基础上,通过综合利用随机混合整数规划方法,进一步提出了针对上述评价指标的具体计算方法。最后,以某一工业园区负荷为例,对所提评估框架进行有效性验证。仿真结果表明,所提方法在保证智能楼宇正常运行前提下可充分发掘智能楼宇的能源供应潜力,有效提升配电系统在极端灾害下的供能可靠性。

关键词: 智能楼宇, 分布式电源, 冗余度支撑, 电网弹性, 供能可靠性

Abstract:

As an important type of load-side resources, the distributed generation (DG) is widely used in smart buildings to provide new possibilities for rapid power supply recovery and load transfer after extreme disasters. This paper proposed a comprehensive evaluation framework for the smart building load restoration, which is used to quantitatively analyze and calculate the transfer capacity of the DG supply at the end of the smart buildings to the critical load in the distribution system after extreme disaster.On the basis of modeling different types of physical equipment in smart buildings, the multi-energy complementary and energy coupling characteristics were considered. Firstly, three quantitative evaluation indexes including electric power transfer amount, heat transfer amount and cooling transfer amount were proposed. The contribution of smart building power to system load recovery after extreme disasters was accurately quantified. On this basis, the specific calculation method for the above evaluation indicators was further proposed via using the random mixed integer programming method. Finally, taking the load of an industrial park as an example, the validity of the evaluation framework proposed was verified. The simulation results demonstrate that the proposed method can fully explore the energy supply potential of smart buildings with ensuring the normal operation of smart buildings, and effectively improve the reliability of power distribution systems under extreme disasters.

Key words: smart buildings, distributed generation, redundancy support, power grid resilience, energy supply reliability