Open AccessResearch on optimization of primary frequency regulation of thermal power units based on multi-model predictive control
Author(s) -
Aimin Gao,
Xiaobo Cui,
Guoqiang Yu,
Jianjun Shu,
Xiaolong Yang,
Tianhai Zhang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/675/1/012082
Subject(s) - control theory (sociology) , frequency regulation , thermal power station , robustness (evolution) , overshoot (microwave communication) , model predictive control , electric power system , nonlinear system , automatic frequency control , computer science , control engineering , steam turbine , power (physics) , power control , automatic generation control , engineering , control (management) , telecommunications , mechanical engineering , biochemistry , physics , chemistry , quantum mechanics , artificial intelligence , gene , waste management
The nonlinear problem of system cannot be well solved using traditional power regulation system, which causes regulation lag and insufficient output and poor accuracy of the actual performance of the primary frequency regulation (PFR) on thermal power units. In order to further improve PFR performance of thermal power units, a multi-model predictive control method is adopted to optimize and improve the traditional steam turbine power control system. A PFR optimal control strategy is proposed, which improves the regulation performance and robustness of the power control system. The simulation results show that the proposed optimization algorithm can overcome the nonlinear problem of the steam turbine governing valve, and the regulating process is stable and fast without overshoot. This research is of great significance to improve the contribution rate of PFR of thermal power units and to better satisfy the assessment of power grid PFR, thereby to stabilize the frequency of power grid.