Flexibility-Oriented AC/DC Hybrid Grid Optimization Using Distributionally Robust Chance-Constrained Method

Yue Chen (), Qiuyu Lu, Kaiyue Zeng, Yinguo Yang and Pingping Xie
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Yue Chen: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Qiuyu Lu: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Kaiyue Zeng: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Yinguo Yang: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Pingping Xie: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China

Energies, 2024, vol. 17, issue 19, 1-18

Abstract: With the increasing integration of stochastic sources and loads, ensuring the flexibility of AC/DC hybrid distribution networks has become a pressing challenge. This paper aims to enhance the operational flexibility of AC/DC hybrid distribution networks by proposing a flexibility-oriented optimization framework that addresses the growing uncertainties. Notably, a comprehensive evaluation method for operational flexibility assessment is first established. Based on this, this paper further proposes a flexibility-oriented operation optimization model using the distributionally robust chance-constrained (DRCC) method. A customized solution method utilizing second-order cone relaxation and sample average approximation (SAA) is also introduced. The results of case studies indicate that the flexibility of AC/DC hybrid distribution networks is enhanced through sharing energy storage among multiple feeders, adaptive reactive power regulation using soft open points (SOPs) and static var compensators (SVCs), and power transfer between feeders via SOPs.

Keywords: AC/DC hybrid distribution network; distributionally robust chance-constrained; flexibility; optimal scheduling strategy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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