Flexibility planning of transmission grid based on correlation of generation and transmission

3rd International Conference on Energy Engineering and Environmental Protection

能源学;生态环境科学

Li, Ting^1 ; Ye, Xi^1 ; Zhu, Mi^1 ; Ouyang, Xuetong^1 ; Liu, Wanyu^2 ; Li, Huaqiang^2

State Grid Sichuan Economic Rresearch Institute, Chengdu

610041, China^1

College of Electrical Engineering and Information Technology, Sichuan University, Chengdu

610065, China^2

关键词: Flexibility index;    Planning models;    Power generation technology;    Programming models;    Security and stability;    Space-time coupling;    Supply and demand balances;    Transmission grids;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/227/2/022018/pdf
DOI  :  10.1088/1755-1315/227/2/022018

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The sharp development of power generation technology involving the clean energy boosts the grid-connected proportion of clean power such as wind and light, whereas the randomness and volatility of their outputs contribute to the strong uncertainty of multi-space-time coupling in the power system, seriously affecting the security and stability of the power grid. Hence, the traditional grid planning has been unable to meet the needs of high proportion of grid-connected clean energy. However, the flexibility of the power system can effectively reflect the system's ability to withstand the impact of uncertainty and is of great significance to the integration of the high proportion of clean energy. Based on the original definition of flexibility, this paper proposes a flexibility index system considering supply and demand balance, grid layout and power flow distribution, and comprehensively evaluates the power system's acceptance of clean energy. Besides, a two-level extended programming model of transmission network with flexibility index system is established. The improved chaotic crossover genetic algorithm is used to solve the planning model. The feasibility and practicability of the proposed index system and planning model are verified by the simulation of the Garver-18 node system respectively.