Aggregated regulation and coordinated scheduling of PV-storage integrated 5G base stations considering PV-load uncertainty

被引:1
|
作者
Li, Congfei [1 ]
Liu, Jiayi [1 ]
Ding, Tian [1 ]
Liu, Xi [1 ]
Zhou, Zhenyu [1 ]
Sun, Zhongwei [1 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, State Key Lab Alternate Elect Power Syst Renewable, Beijing 102206, Peoples R China
关键词
PV-storage integrated 5G base station; PV-load uncertainty; IGDT; Consensus algorithm; Aggregated regulation and coordinated; scheduling; POWER; ENERGY; COST;
D O I
10.1016/j.ijepes.2024.110306
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Photovoltaic (PV)-storage integrated 5G base station (BS) can participate in demand response on a large scale, conduct electricity transaction and provide auxiliary services, thus reducing the high electricity consumption of 5G BSs and increasing the flexibility resource capacity of the distribution network. However, the flexible resource regulation of PV-storage integrated 5G BSs still faces problems such as many regulators, ignored PV-load uncertainty, and poor adaptability of existing regulatory frameworks and scheduling methods, which leads to greater security operation risks in resource regulation decisions and affects the exploitation of the 5G BSs scheduling potential. Aiming at the above problems, this paper proposes an aggregated regulation and coordinated scheduling method of PV-storage integrated 5G BSs considering PV-load uncertainty. Firstly, a hierarchical cluster-cooperative aggregated regulation framework for the scale PV-storage integrated 5G BSs is established, and a regional communication operator (RCO) schedulable capability model and an information gap decision theory (IGDT) based PV-load uncertainty model are built. Next, a two-stage joint optimization problem is proposed for maximizing the RCO income while reducing the BS cluster operation cost. Then, the first-stage dayahead transaction optimization problem in the electricity market is solved, and the reliable operation planning and economic operation planning strategies are proposed based on IGDT to adapt to the regulation demand under different uncertainty risks; the second-stage BS cluster real-time operation optimization problem is solved based on the adaptive consensus algorithm considering scheduling preferences (ACSP), achieving distributed real-time coordinated scheduling of multiple agents in the BS cluster. Finally, the effectiveness of the proposed method is verified by simulation examples, which show that the aggregated regulation and coordinated scheduling of PV-storage integrated 5G BSs can achieve mutual benefits for the distribution network and communication operators.
引用
收藏
页数:15
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