Open AccessProactive frequency control based on ultra‐short‐term power fluctuation forecasting for high renewables penetrated power systems
Author(s) -
Wen Shuli,
Wang Yu,
Tang Yi,
Xu Yan,
Li Pengfei
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2019.0234
Subject(s) - renewable energy , electric power system , control theory (sociology) , automatic frequency control , computer science , frequency deviation , term (time) , power (physics) , anticipation (artificial intelligence) , control signal , power control , control (management) , engineering , control system , electrical engineering , telecommunications , artificial intelligence , physics , quantum mechanics
The rapidly increasing penetration of renewable energies has introduced severe challenges to power system frequency controls due to the highly intermittent and uncertain power output of renewable energies. This study proposes a proactive frequency control method to control traditional synchronous generators in advance in anticipation of sudden power fluctuation. Therefore, the frequency deviations can be well mitigated by such early‐acted control signal. In order to obtain this new control reference, an ensemble‐forecasting model based on the extreme learning machine algorithm is designed to predict ultra‐short‐term power fluctuations, which serves as an extra signal for automatic generation control. The proposed method was verified on an equivalent model of the Singapore power system with various types of generations and loads. The simulation results clearly demonstrate the accuracy of the forecasting model and the advantages of the proposed control method. The proposed method can also reduce the frequency charging/discharging of energy storage systems, which can effectively extend their lifetime.