Optimal Configuration of the UPFCs and HVRs in City's High-Voltage Power Grid

• Published in: 2025 7th International Conference on Energy Systems and Electrical Power (ICESEP) pp. 18 - 24
• Main Authors: Lin, Guihui, Du, Chengtao, Zhang, Yong, Liu, Xingjian, Wang, Chao, Feng, Mingqian, Luo, Zhiling, Mao, Anjia
• Format: Conference Proceeding
• Language: English
• Published: IEEE 20.06.2025
• Subjects: High Voltage Reactor; High-voltage techniques; Improved Particle Swarm Algorithm; Inductors; Load flow; Nonlinear equations; Nonlinear Mixed-Integer Programming; Particle swarm optimization; Power grids; Programming; Regulation; Robustness; Two-stage optimization; Unified Power Flow Controller (UPFC); Voltage control
• DOI: 10.1109/ICESEP66633.2025.11155570

With the continuous increase in load density and the growing prevalence of cable applications, active power flow and reactive voltage control in urban high-voltage power grids have become more challenging. Traditional single-device optimization methods struggle to balance dynamic regulation capability and economic requirements, while existing joint configuration studies are mostly based on a single approach. To address this, this paper proposes a two-stage optimization configuration framework to achieve coordinated configuration of a Unified Power Flow Controller (UPFC) and high-voltage reactors. In the first stage, based on maximum, minimum, and average load scenarios, power flow margin analysis is used to screen out overloaded lines and nodes. The feasibility of UPFC regulation is verified by solving nonlinear equations, and preliminary configuration schemes are generated based on reactor capacity formulas. In the second stage, a mixed-integer programming model is constructed with the objective of minimizing total investment and operational costs, and a heuristic search strategy is embedded to solve for the global optimal solution in terms of device placement and capacity allocation. The proposed method enhances robustness through a union strategy for typical scenarios and leverages the dynamic-static complementarity between UPFCs and reactors to reduce redundant investment. Finally, the model and method are validated using a modified New England 10-machine 39-bus system case study.