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Aliasghar Ghadimi

Aliasghar Ghadimi

Academic rank: Associate Professor
ORCID: https://orcid.org/0000-0001-7276-2221
Education: PhD.
ScopusId: 56678490500
HIndex:
Faculty: Engineering
Address: Arak University
Phone: 08632625620

Research

Title
Comprehensive enhanced Newton Raphson approach for power flow analysis in droop-controlled islanded AC microgrids
Type
JournalPaper
Keywords
Droop-controlled islanded microgrids Newton Raphson Power flow
Year
2022
Journal International Journal of Electrical Power & Energy Systems
DOI
Researchers Mohammad Bayat ، Masoud Mehrabi ، Aliasghar Ghadimi ، Marcos Tostado Veliz ، Francisco Jurado

Abstract

One of the essential studies in the planning and operation of a microgrid is Power Flow (PF). Traditional PF methods are not applicable for droop-controlled islanded microgrids due to the absence of a slack bus in the system. The steady state characteristics of the system such as frequency, bus voltages, Distributed Generators’ (DG) output power, and actual loads’ demand are obtained based on the droop characteristics of the DGs, and also, the frequency and voltage dependency of the load. Therefore, in this paper, an Enhanced Newton Raphson (ENR) method is proposed for PF in the droop-controlled islanded microgrids. The proposed method is based on the well-known NR method but with a more comprehensive model that considers different droop schemes (resistive, inductive, and complex), load demand dependency on voltage and frequency, π line model, and shunt compensators. Moreover, a new index for selecting proper droop characteristics for any droop-controlled islanded microgrid is proposed. Five test systems with different scales, topologies, droop control strategies, and various load models are considered to evaluate the performance of the proposed method. The results are compared with the recently developed methods and steady-state results of Time-Domain simulations conducted in PLECS software. The results show that the proposed technique has excellent accuracy with low computational time and can be easily integrated into the currently available power system analysis tools.