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Self-organizing Droop Control of Multi-terminal DC Distribution Network Considering Power Margin and Voltage Deviation
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Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education(Northeast Electric Power University), Jilin 132012, China

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    Abstract:

    In order to realize the optimal allocation of unbalanced power and the stable control of DC voltage after disturbance, this paper proposes a self-organizing droop characteristic optimization method considering power margin and additional constant DC voltage control based on the conventional voltage and power droop control of multi-terminal flexible DC distribution network. The proposed method breaks the inherent constraint that the unbalanced power of converter station is proportionally distributed according to its capacity in the conventional droop control, which realizes the rational transfer of unbalanced power and reduces the overload risk of smaller-capacity converter stations. By introducing the power deviation factor, the “dead zone” is appropriately set on the droop characteristic curve to relax the operation range of the converter station to a certain extent. By analogy to the concept of elasticity mechanics, this paper designs a self-organizing updating rule of operation state of the converter station based on the cellular automaton. The corresponding MATLAB simulation model of five-terminal DC distribution network is established, and the proposed model is compared with the electromagnetic transient model with traditional droop control. Finally, the simulation results verify the effectiveness and control effects of the proposed control method.

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CHENG Long, JIN Guobin, WANG Limeng,et al.Self-organizing Droop Control of Multi-terminal DC Distribution Network Considering Power Margin and Voltage Deviation[J].Automation of Electric Power Systems,2019,43(23):81-89.DOI:10.7500/AEPS20190419005

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History
  • Received:April 19,2019
  • Revised:October 24,2019
  • Adopted:September 20,2019
  • Online: October 23,2019
  • Published: