Day-Ahead and Intraday Joint Optimal Dispatch in Active Distribution Network Considering Centralized and Distributed Energy Storage Coordination

In active distribution network (ADN), there exist significant differences in the characteristics of different types of energy storage, leading to coordination challenges. This makes it difficult to effectively address power fluctuation issues caused by the substantial integration of renewable energy...

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Bibliographic Details
Published in:IEEE transactions on industry applications Vol. 60; no. 3; pp. 4832 - 4842
Main Authors: Wang, Guoying, Wang, Chengfu, Feng, Tianyuan, Wang, Kang, Yao, Wenliang, Zhang, Zhaosong
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Active distribution network
Algorithms
consistency algorithm
Coordination
Distribution networks
Energy storage
energy storage coordination strategy
Fluctuations
Job shop scheduling
optimal dispatch
Optimal scheduling
Optimization
Renewable energy sources
Scheduling
scheduling framework
ISSN:0093-9994, 1939-9367
Online Access:Get full text
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Summary:In active distribution network (ADN), there exist significant differences in the characteristics of different types of energy storage, leading to coordination challenges. This makes it difficult to effectively address power fluctuation issues caused by the substantial integration of renewable energy sources (RESs). To this end, a day-ahead and intraday joint optimal dispatch method in ADN, which includes an energy storage coordination strategy and a scheduling framework, is proposed in this paper. The energy storage coordination strategy can schedule centralized and distributed energy storage (CES and DES) according to their differences in capacity and response speed. CES is used as energy-type energy storage to take part in the peak shaving of ADN, while DES is used as power-type energy storage to smooth out the rapid power fluctuation of RES. The scheduling framework is divided into two stages: day-ahead and intraday. In the day-ahead stage, the operation state of CES and other slow-response resources is optimized and determined. In the intraday stage, the rough output of the fast-response DES, is optimized based on the short-term prediction. Subsequently, a consistency algorithm is utilized for optimizing the rough output of DES to obtain the precise output state. Further, the scheduling framework uses the schedulable margin of DES as a feedback signal to optimize the output status of CES. A case study on an IEEE 33-bus system verifies the effectiveness of the proposed method.
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ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2024.3372943