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计及源—荷时空相关性的主动配电网分布式优化调度
作者:
作者单位:

1. 东南大学电气工程学院, 江苏省南京市 210096; 2. 江苏省智能电网技术和装备重点实验室, 江苏省南京市 210096; 3. 国网江苏省电力有限公司南通供电公司, 江苏省南通市 226001

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基金项目:

国家自然科学基金资助项目(51707033);国网江苏省电力有限公司科技项目(J2019100)


Distributed Optimal Dispatch of Active Distribution Network Considering Source-Load Temporal and Spatial Correlations
Author:
Affiliation:

1. School of Electrical Engineering, Southeast University, Nanjing 210096, China; 2. Jiangsu Provincial Key Laboratory of Smart Grid Technology & Equipment, Nanjing 210096, China; 3. Nantong Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Nantong 226001, China

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    摘要:

    首先,建立不同光伏之间以及光伏与负荷之间的相关性约束,并利用拉丁超立方抽样和Cholesky分解技术相结合的处理方法对该非线性的相关性约束进行场景化分析。其次,建立主动配电网分布式优化模型。由于配电网和微电网联络线上存在有功无功功率以及临界节点电压耦合关系,采用复制节点的区域分解方法实现配电网和微电网的解耦。在此基础上,引入目标级联分析法实现配电网和微电网之间的迭代求解。最后,采用改进的IEEE 123节点作为算例对所提模型进行了验证,并着重研究源—荷时空相关性对优化结果的影响。

    Abstract:

    Firstly, the correlation constraints between different photovoltaic(PV)units and between PV and load are established. Latin hypercube sampling and Cholesky decomposition are introduced to describe the nonlinear correlation constraints using the scenario analysis method. Then, the optimal scheduling model of active distribution network and microgrid is established respectively. Due to the coupling relationship of active power and threshold bus voltage on the tie-line between distribution network and microgrid, the region decomposition method is employed to decouple distribution network and microgrid. Then the proposed distribution optimization model is solved by analysis target cascading(ATC). Finally, the modified IEEE 123 bus system is adopted to demonstrate the effectiveness and convergence of the proposed model. The influence of source-load temporal and spatial correlation is analyzed.

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赵毅,吴志,钱仲豪,等.计及源—荷时空相关性的主动配电网分布式优化调度[J].电力系统自动化,2019,43(19):68-76. DOI:10.7500/AEPS20190423003.
ZHAO Yi, WU Zhi, QIAN Zhonghao,et al.Distributed Optimal Dispatch of Active Distribution Network Considering Source-Load Temporal and Spatial Correlations[J].Automation of Electric Power Systems,2019,43(19):68-76. DOI:10.7500/AEPS20190423003.

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  • 收稿日期:2019-04-23
  • 最后修改日期:2019-08-14
  • 录用日期:2019-05-28
  • 在线发布日期: 2019-08-06
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