Open AccessHigh penetrated renewable energy sources‐based AOMPC for microgrid's frequency regulation during weather changes, time‐varying parameters and generation unit collapse
Author(s) -
Abazari Ahmadreza,
Soleymani Mohammad Mahdi,
Babaei Masoud,
Ghafouri Mohsen,
Monsef Hassan,
Beheshti Mohammad T. H.
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.0074
Subject(s) - control theory (sociology) , microgrid , pid controller , inertia , controller (irrigation) , turbine , automatic frequency control , renewable energy , electric power system , computer science , wind power , fuzzy logic , control engineering , engineering , power (physics) , control (management) , temperature control , mechanical engineering , telecommunications , agronomy , classical mechanics , quantum mechanics , electrical engineering , biology , physics , artificial intelligence
Using inverter‐based topologies and lack of rotational masses can lead to a noticeable reduction in the inertia of modern systems and have detrimental effects on the resiliency, stability and strengths of microgrids. Effective frequency control ancillary services and modern adaptive control mechanisms can be proposed to resolve the mentioned challenges practically. From this perspective, several flexible and intelligent control approaches have been recently introduced to create a balance between generation and load demand during various operational conditions in low‐inertia power systems. This study suggests a supportive collaboration between two distributed generations including virtual inertia of wind turbine generator and fast speed micro‐turbine based on an adaptive optimal model predictive control (AOMPC). To demonstrate the effectiveness of the proposed framework, the results are compared with the previous controllers like optimal proportional–integral, optimal fractional order proportional–integral–derivative (PID), optimal fuzzy PID, the optimised membership function of fuzzy and adaptive MPC controller during multiple load variations, changes in the weather patterns, unwanted time‐varying uncertainties and collapse of power generation units.