Open AccessReduced‐order dynamic model for droop‐controlled inverter/converter‐based low‐voltage hybrid AC/DC microgrids – Part 2: DC sub‐microgrid and power exchange
Author(s) -
Rasoolzadeh Arsalan,
Salmasi Farzad Rajaei
Publication year - 2018
Publication title -
iet smart grid
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.612
H-Index - 11
ISSN - 2515-2947
DOI - 10.1049/iet-stg.2018.0070
Subject(s) - microgrid , voltage droop , control theory (sociology) , power (physics) , inverter , matlab , controller (irrigation) , computer science , fault (geology) , voltage , constant (computer programming) , ac power , engineering , electrical engineering , physics , voltage source , control (management) , agronomy , quantum mechanics , artificial intelligence , biology , operating system , seismology , geology , programming language
This study focuses on reduced‐order dynamical modelling of droop controlled converter‐based DC sub‐microgrid (MG) in a hybrid AC/DC MG. In hybrid MGs, electrical power is exchanged between the AC and DC sub‐MGs by a bidirectional AC/DC converter. The authors aim to develop a comprehensive reduced‐order dynamical model for the DC side in this part, incorporating standard classes of electrical loads including constant current, constant power, and constant resistance loads. Furthermore, dynamical behaviour of the power exchange between the AC and DC sub‐MGs is modelled, considering that the bidirectional power converter controller aims to equalise the load ratios of AC and DC sub‐MGs in order to facilitate overall decentralised control over the hybrid MG. Analytical derivations of steady‐state values of main variables are given and the overall dynamical and algebraic equations are determined. In order to validate the developed model, a hybrid MG is implemented in PSCAD. Then, the proposed model for the case study is implemented in Matlab/Simulink and the results are compared with the PSCAD outputs. The comparative results show the validity of the developed reduced‐order comprehensive model. The reduced‐order models are preferred in designing observers such as model‐based fault detection and diagnosis observers.