Bi-layer Uncertainty Economic Scheduling for Port Multi-energy Microgrid with Cascade Utilization of Cold Energy

被引：0

作者：

Hou H. ^{[1
,2
]}

Xie Y. ^{[1
,2
]}

Gan M. ^{[1
,2
]}

Zhao B. ^{[3
]}

Zhang L. ^{[3
]}

Xie C. ^{[1
,2
]}

机构：

[1] School of Automation, Wuhan University of Technology, Wuhan

[2] Shenzhen Research Institute, Wuhan University of Technology, Shenzhen

[3] Electric Power Research Institute of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 06期

基金：

中国国家自然科学基金;

关键词：

cascade utilization; cold energy; distributionally robust optimization; economic scheduling; microgrid; multi-time-scale optimization; port; temporal correlation; uncertainty; wind power;

D O I：

10.7500/AEPS20230721001

中图分类号：

学科分类号：

摘要：

To effectively exploit the low-carbon flexibility potential of liquified natural gas (LNG) cold energy utilization in ports and give full play to the synergistic optimization effects across multiple time scales, a robust-stochastic bi-layer uncertainty economic scheduling model for port multi-energy microgrid (MEMG) considering the cascade utilization of LNG cold energy is proposed. Firstly, considering the low-carbon flexibility potential of LNG cold energy utilization across each deep cooling-mid cooling-shallow cooling temperature zone, a cold energy cascade utilization model of low-temperature carbon capture, cold energy power generation, and direct cooling is established, and a collaborative carbon processing of capture-storage-utilization is formed on this basis. Secondly, the wind power scenarios considering the temporal correlation of prediction errors are generated based on the equal probability inversion, and the scenarios are reduced by using a 0-1 planning model based on the Wasserstein distance. Thirdly, concerning the characteristic of wind power prediction error increasing with the increase of time scale, a robust-stochastic bi-layer uncertainty economic scheduling model with multi-time-scale optimization is constructed. The upper layer guarantees the robustness of day-ahead pre-scheduling decisions through distributionally robust optimization, and the lower layer guarantees the economic benefits of intra-day rolling scheduling decisions through stochastic optimization. Finally, the simulation results demonstrate that the proposed robust-stochastic bi-layer scheduling model considering the cold energy cascade utilization can not only better solve the contradiction of low prediction accuracy on day-ahead long-time-scale and easy to fall into the local optimum on intra-day short-time-scale, but also provide more economy, low-carbon emissions and power supply flexibility to the port MEMG. © 2024 Automation of Electric Power Systems Press. All rights reserved.

引用

页码：205 / 215

页数：10

共 21 条

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