Open AccessReal‐time optimisation of emergency demand response and HVDC power modulation to improve short‐term frequency stability of the receiving‐end power systems
Author(s) -
Wang Luping,
Xie Xiaorong,
Peng Long,
Hu Yinghong,
Zhao Yuan
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8682
Subject(s) - automatic frequency control , control theory (sociology) , computer science , frequency response , electric power system , demand response , stability (learning theory) , blackout , term (time) , power (physics) , electricity , high voltage direct current , control (management) , voltage , engineering , telecommunications , direct current , electrical engineering , physics , quantum mechanics , artificial intelligence , machine learning
In recent years, large‐capacity high‐voltage direct currents (HVDCs) have been employed to transfer electricity from the west to the east of China. However, the frequent frequency drops due to HVDC blockings seriously threaten the short‐term frequency stability of receiving‐end power systems. The existing emergency frequency control strategy is not adaptive to the varying operation conditions and may cause excessive or deficient actions, which could result in inefficient control or high risk of frequency instability. Therefore, a real‐time coordinated control strategy is proposed in this study based on the online‐updated frequency response model. The model is designed to incorporate multiple types of generators and to reflect the dynamic frequency response of loads. The new control strategy combines multiple control resources, including the emergency demand response and HVDC power modulation, to improve the short‐term frequency stability after HVDC failures. By online data preparation and cubic fitting, the nadir of the frequency is expressed as an analytic function of the control variables. A real‐time optimisation of emergency controls is achieved to improve the short‐term frequency dynamics. Case studies show that the proposed scheme is robust to the varying operation conditions and has lower control cost than the existing control strategy.