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

doi:10.12096/j.2096-4528.pgt.19081

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

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

Energy Internet | 更新时间：2025-06-06

- Evaluation on Load Restoration of Distribution System Based on Distributed Generation in Smart Buildings After Extreme Disasters
- Power Generation Technology Vol. 40, Issue 5, Pages: 440-447(2019)
- 作者机构：
  
  新能源电力系统国家重点实验室(华北电力大学), 北京市昌平区 102206
- 作者简介：
- 基金信息：
  
  Fundamental Research Funds for the Central Universities(2017MS007)
- DOI：10.12096/j.2096-4528.pgt.19081
  CLC：
- Received：20 May 2019，
  
  Published：30 October 2019
- 稿件说明：
移动端阅览
Wei FANG, Bo ZENG, Fuqiang XU, et al. Evaluation on Load Restoration of Distribution System Based on Distributed Generation in Smart Buildings After Extreme Disasters[J]. Power Generation Technology, 2019, 40(5): 440-447.
DOI：

Wei FANG, Bo ZENG, Fuqiang XU, et al. Evaluation on Load Restoration of Distribution System Based on Distributed Generation in Smart Buildings After Extreme Disasters[J]. Power Generation Technology, 2019, 40(5): 440-447. DOI： 10.12096/j.2096-4528.pgt.19081.

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。

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.

关键词

Keywords

references

郭庆来, 辛蜀骏, 王剑辉, 等.由乌克兰停电事件看信息能源系统综合安全评估[J].电力系统自动化, 2016, 40(5):145-147.

薛禹胜, 肖世杰.综合防御高风险的小概率事件:对日本相继天灾引发大停电及核泄漏事件的思考[J].电力系统自动化, 2011, 35(8):1-11.

晏鸣宇, 周志宇, 文劲宇, 等.基于短期覆冰预测的电网覆冰灾害风险评估方法[J].电力系统自动化, 2016, 40(21):168-175.

高海翔, 陈颖, 黄少伟, 等.配电网韧性及其相关研究进展[J].电力系统自动化, 2015, 39(23):1-8.

别朝红, 林雁翎, 邱爱慈.弹性电网及其恢复力的基本概念与研究展望[J].电力系统自动化, 2015, 39(22):1-9.

Lin Y L, Bie Z H.Study on the resilience of the integrated energy system energy procedia[J].2016, 103: 171-176.

Panteli M, Mancarella P.Modeling and evaluating the resilience of critical electrical power infrastructure to extreme weather events[J].IEEE Systems Journal, 2015:1-10.

Ma S S, Chen B K, Wang Z Y.Resilience enhancement strategy for distribution systems under extreme weather events[J].IEEE Transactions on Smart Grid, 2018, 9(2):1442-1451.

靳小龙, 穆云飞, 贾宏杰, 等.融合需求侧虚拟储能系统的冷热电联供楼宇微网优化调度方法[J].中国电机工程学报, 2017, 37(2):581-590.

于秩彬, 王春芳, 周钊正, 等.青岛地区四季天气对光伏发电量的影响[J].广东电力, 2019, 32(6):48-54.

李沐珂, 张靠社.计及分布式光伏发电的分时电价模型研究[J].电网与清洁能源, 2018, 34(4):74-78.

刘金裕, 赵磊, 朱道立.基于LASSO的光伏发电功率短期时间序列预测[J].电力科学与工程, 2019, 35(7):13-22.

邓得政, 刘畅, 李庚银.直流配电网经济调度方法研究[J].分布式能源, 2018, 3(2):39-46.

杜炬虎, 刘静.园区燃气分布式能源站微电网结构解析[J].华电技术, 2019, 41(3):23-25, 28.

Wang Y, Chen C, Wang J, et al.Research on resilience of power systems under natural disasters:a review[J].IEEE Transactions on Power Systems, 2016, 31(2):1604-1613.

曾鸣, 刘英新, 周鹏程, 等.综合能源系统建模及效益评价体系综述与展望[J].电网技术, 2018, 42(6):1697-1708.

郭尊, 李庚银, 周明, 等.计及综合需求响应的商业园区能量枢纽优化运行[J].电网技术, 2018, 42(8):2439-2448.

陈厚合, 李泽宁, 靳小龙, 等.集成智能楼宇的主动配电网建模及优化方法[J].中国电机工程学报, 2018, 38(22):6550-6563.

艾欣, 陈政琦, 孙英云, 等.基于需求响应的电-热-气耦合系统综合直接负荷控制协调优化研究[J].电网技术, 2019, 43(4):1160-1171.

张义志, 王小君, 和敬涵, 等.考虑供热系统建模的综合能源系统最优能流计算方法[J].电工技术学报, 2019, 34(3):562-570.

顾伟, 陆帅, 王珺, 等.多区域综合能源系统热网建模及系统运行优化[J].中国电机工程学报, 2017, 37(5):1305-1316.

王成山, 洪博文, 郭力, 等.冷热电联供微网优化调度通用建模方法[J].中国电机工程学报, 2013, 33(31):26-33.

朱永强, 王甜婧.交直流混合微电网网络坚强度评估的指标体系及方法[J].电网技术, 2018, 42(2):455-463.

吕朋蓬, 赵晋泉, 李端超, 等.电网运行状态评价指标体系与综合评价方法[J].电网技术, 2015, 39(8):2245-2252.

齐世雄, 王秀丽, 邵成成, 等.极端事件下电-气混联综合能源系统的恢复力分析[J].电网技术, 2019, 43(1):41-51.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on Fault Location in Integrated Energy Systems Based on Improved Binary Particle Swarm Optimization Algorithm

Optimal Configuration of Distributed Generation Considering Carbon Trading and Reactive Power Compensation

Overview of Active Distribution Network Planning With High Proportion of New Energy Access

A Post-evaluation Index System of Active Distribution Network Project and Its Comprehensive Evaluation Method

Related Author

REN Mingwei

SUN Yuxin

DU Yi

XU Peifeng

GONG Yifan

SHI Kai

LIU Jie

GAO Yang

Related Institution

College of Electrical Information Engineering, Jiangsu University

Changxing Power Supply Company of State Grid Shanghai Electric Power Company, Chongming District

Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Shanghai Jiao Tong University), Minhang District

School of Electrical Engineering, Northeast Electric Power University

Three Gorges New Energy Offshore Wind Power Operation and Maintenance of Jiangsu Co., Ltd.

AI问答

⁰