1. Enhancing distribution system stability and efficiency through multi‐power supply startup optimization for new energy integration
- Author
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Qinglin Meng, Xinyu Tong, Sheharyar Hussain, Fengzhang Luo, Fei Zhou, Ying He, Lei Liu, Bing Sun, and Botong Li
- Subjects
high proportion of renewable energy ,inertia support ,reinforcement learning ,primary frequency modulation ,multi‐power supply ,collaborative optimization ,Distribution or transmission of electric power ,TK3001-3521 ,Production of electric energy or power. Powerplants. Central stations ,TK1001-1841 - Abstract
Abstract 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.
- Published
- 2024
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