Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Distributed Optimal Voltage Control for Multi-terminal Direct Current System with Large-scale Wind Farm Cluster Based on ADMM
Author:
Affiliation:

1.College of Electrical and Information Engineering, Hunan University, Changsha, China;2.Guangdong Power Grid Co., Ltd., Dongguan, China;3.School of Electronics, Electrical Engineering, and Computer Science, Queen’s University Belfast, BT8 5BN, Belfast, UK

Fund Project:

This work was supported by the National Key R&D Program of China (No. 2022YFF0608700).

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    Abstract:

    The power loss minimization and DC voltage stability of the multi-terminal direct current (MTDC) system with large-scale wind farm (WF) cluster affect the stability and power quality of the interconnected power grid. This paper proposes a distributed optimal voltage control (DOVC) strategy, which aims to optimize voltage distribution in MTDC and WF systems, reduce system power losses, and track power dispatch commands. The proposed DOVC strategy employs a bi-level distributed control architecture. At the upper level, the MTDC controller coordinates power flow, DC-side voltage of grid-side voltage source converters (GSVSCs), and WF-side voltage source converters (WFVSCs) for power loss minimization and DC voltage stabilization of the MTDC system. At the lower level, the WF controller coordinates the controlled bus voltage of WFVSC and the active and reactive power of wind turbines (WTs) to maintain WT terminal voltages within feasible range. Then, the WF controller minimizes the power loss of the WF system, while tracking the optimal command from the upper-level control strategy. Considering the computational tasks of multi-objective optimization with large-scale WF cluster, the proposed DOVC strategy is executed in a distributed manner based on the alternating direction method of multipliers (ADMM). An MTDC system with large-scale WF cluster is established in MATLAB to validate the effectiveness of the proposed DOVC strategy.

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History
  • Received:March 19,2024
  • Revised:July 05,2024
  • Online: May 27,2025