z-logo
open-access-imgOpen Access
Current injection‐based Newton–Raphson power‐flow algorithm for droop‐based islanded microgrids
Author(s) -
Kumar Abhishek,
Jha Bablesh Kumar,
Singh Devender,
Misra Rakesh Kumar
Publication year - 2019
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.2019.0575
Subject(s) - voltage droop , slack bus , robustness (evolution) , newton's method , microgrid , control theory (sociology) , algorithm , electric power system , computer science , power flow , convergence (economics) , power (physics) , voltage , ac power , power flow study , mathematics , mathematical optimization , engineering , nonlinear system , voltage source , control (management) , artificial intelligence , physics , electrical engineering , economic growth , chemistry , biochemistry , economics , gene , quantum mechanics
The power‐flow analysis of droop‐based islanded microgrid (DBIMG) is a growing research area. The conventional power‐flow techniques have been difficult to employ in DBIMG due to the non‐existence of reference bus (slack bus). To address this issue, a current injection Newton–Raphson based novel algorithm is proposed. The proposed algorithm chooses system frequency and voltage magnitude of the reference bus as additional variables in power‐flow formulation. The proposed algorithm takes into account three operating modes of distributed generators viz. Droop control, PQ and PV . The linear equations cover the droop characteristics of the DGs, while non‐linear equations cover power‐flow equations of the system. The proposed algorithm has been executed on two test systems viz. 6‐bus system and 38‐bus system. To show the effectiveness and robustness of the proposed algorithm, the performance of the proposed algorithm is also examined for the different loading conditions and different R/X ratios of the line of the test systems. The obtained solutions have also been compared with the solutions obtained by other Newton–Raphson based algorithms reported in the literature and PSCAD. The comparative analysis shows better efficiency and superior convergence of the proposed algorithm.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here