Enhancing distribution system stability and efficiency through multi-power supply startup optimization for new energy integration

被引:50
作者
Meng, Qinglin [1 ,2 ,3 ,4 ]
Tong, Xinyu [1 ]
Hussain, Sheharyar [5 ]
Luo, Fengzhang [3 ]
Zhou, Fei [6 ]
He, Ying [2 ]
Liu, Lei [1 ]
Sun, Bing [3 ]
Li, Botong [3 ]
机构
[1] State Grid Tianjin Elect Power Co, State Grid Corp China, Tianjin 300010, Peoples R China
[2] Tianjin Renai Coll, Green Power Res Inst, Tianjin 301636, Peoples R China
[3] Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
[4] Tiangong Univ, Sch Elect Engn, Tianjin, Peoples R China
[5] Zhejiang Univ, Inst Marine Elect & Intelligent Syst, Zhoushan 316000, Peoples R China
[6] China Elect Power Res Inst, Inst Comp & Applicat, Beijing, Peoples R China
关键词
high proportion of renewable energy; inertia support; reinforcement learning; primary frequency modulation; multi-power supply; collaborative optimization;
D O I
10.1049/gtd2.13299
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
This paper addresses the challenge of maximizing power capture from new energy sources, including coal, wind, solar, and hydroelectric power, which often lack sufficient inertia support. This deficiency can lead to frequency instability and cascading failures within the power system. A cooperative optimization model for the start-up of multiple power supplies, designed to enhance the integration of new energy sources while maintaining system stability is proposed. The model incorporates primary frequency modulation and the intrinsic inertia support capabilities of self-synchronous voltage source field stations, considering dynamic frequency constraints. Additionally, it employs new energy units with primary frequency modulation to provide inertia support during curtailment, particularly when conventional units cannot meet frequency standards due to existing constraints. Extensive simulations and comparative analyses demonstrate that the proposed model improves new energy utilization by up to 37.5% and reduces operational costs by approximately 16%, enhancing overall operational efficiency in high energy consumption scenarios.
引用
收藏
页码:3487 / 3500
页数:14
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