Day-ahead and Intraday Coordinated Economy Schedule Method Based on the Optimal Operation Region in the Active Distribution Network

被引：0
|
作者：
Wang C. [1 ,2 ]
Fang R. [3 ]
Lei H. [3 ]
Sun J. [1 ,2 ]
Zha X. [1 ,2 ]
机构：
[1] School of Electrical Engineering and Automation, Wuhan University, Hubei Province, Wuhan
[2] Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, Wuhan University, Hubei Province, Wuhan
[3] Economic and Technical Research Institute of State Grid Hubei Electric Power Co., Ltd., Hubei Province, Wuhan
来源：
Dianwang Jishu/Power System Technology | 2024年 / 48卷 / 04期
基金：
中国国家自然科学基金;
关键词：
active distribution network; coordinated scheduling; optimal economic operation region; time-coupling constraints;
D O I：
10.13335/j.1000-3673.pst.2023.0537
中图分类号：
学科分类号：
摘要：
The conventional approach to day-ahead and intraday coordination aims to minimize the disparities between the day-ahead reference planning and the actual intraday operation for devices like energy storage systems (ESS). However, devices tied to the time dynamics, such as the ESSs, have limited intra-day adjustability, leading to poor economy and flexibility. This paper proposes a novel method for day-ahead and intraday coordination using the optimal economic operation region (OEOR) in active distribution networks (ADN). A linearized ADN scheduling model is established in the day-ahead stage. Numerous stochastic scenarios, generated by the Latin hypercube sampling algorithm, yield the optimal sequential curves. To maximize the coverage of optimal outcomes considering the constraints like charging and discharging of the ESS and the climbing and landslide rates of the micro gas turbine generators, a OEOR model is created. In the intraday stage, the outputs of relevant devices are adjusted within the OEOR using the receding-horizon optimization. If the results approach the OEOR bounds and the adjacent period constraints, the region is expanded to the extreme OEOR (E-OEOR). Case studies confirm the method's efficacy, enhancing the ADN economic efficiency compared to the traditional methods. © 2024 Power System Technology Press. All rights reserved.
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页码：1602 / 1611
页数：9
相关论文
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