Coordinated reactive power control of hydro generators in the Nordic grid

被引:0
作者
Melfald, Emil Ghieh [1 ]
Oyvang, Thomas [1 ]
机构
[1] Univ South Eastern Norway, Dept Elect Engn IT & Cybernet, Porsgrunn, Norway
来源
2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM | 2023年
关键词
Multi-machine systems; Reinforcement learning; Optimal control; Voltage control; VOLTAGE;
D O I
10.1109/PESGM52003.2023.10253017
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Hydrogenerators are well known for their voltage control capacity to maintain the Nordic Grid's dynamic security. New methods for coordination between the hydropower fleet and the grid is an unavoidable energy-transitioning strategy. This strategy challenges the current role of the old-fashioned hydrogenerators and demands enhanced coordination beyond the currently implemented technology. This paper proposes a new method to coordinate such multi-machine systems to deliver the required reactive power needed by the grid operator with reduced power losses in the system. Reinforcement Learning (RL) is investigated as a tool for enhancing a reactive power control scheme for multi-machine reactive power support. An in-depth simulation study of a 132 kV radial system from the Norwegian power system is presented, and the overall efficiency improvements are demonstrated on a real-world data set from Nordpool.
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收藏
页数:5
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