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disaster. This notion, however, comes with its own set of
issues, such as quick and precise islanding detection,
effective regulation of voltages and frequencies inside the M-
grid, detecting loss of synchronization and addressing the
overload problems.
Many studies have been conducted in this context by a
lot of researchers to solve the concerns mentioned above,
such as, Wang, J. et al. in 2018 [7] and Zacharia, L et al. in
2019 [8] developed M-grid energy management systems to
schedule the M-grid operation in each time step. In 2020 [9],
Xiaoling Xiong and Yuchen Yang, proposed photovoltaic
based DC microgrid (PVDCM) system which consists of a
solar power system, a battery connected to the common bus
via a boost converter and a bidirectional buck/boost
converter, respectively. While the photovoltaic (PV) panels
may be operating in MPPT mode or constant voltage mode,
electricity can flow bidirectionally between the battery and
the load. In 2020 [10], K. Rajasekhara Reddy et al.
introduced a full examination of the few variants of the grid
connected PV inverter system, as well as its control
technique for tracking maximum power and producing
pulses to achieve the needed output power. In 2020 [11],
Lucas O. Mogaka et al proposed a control method for an
operation of M-grid powered by RERs capable of operating
in both grid connected and islanded modes. When the M-
grid is disconnected from the main grid, the RERs controller
system detects an islanding condition and switches to a
voltage control mode. The interface control is meant to give
consistent active and reactive electricity to the grid in on grid forecasting variations. In 2021 [20], Mwaka I. Juma et al.
mode. After adequate resynchronization, an islanding
detection algorithm will put the inverter into voltage control
mode without harming the important loads if the grid is
unplugged. In 2020 [12], Bilal Naji Alhasnawi and Basil H.
Jasim, employed a home energy management system that
alternates between distributed energy and grid power
sources. The home energy management system includes
controllers for MPPT, battery charge and discharge, and an
inverter for effective regulation between different sources
based on load requirements and source availability at
maximum PowerPoint. In addition, MPPT approach has
been applied to the PV to collect the maximum power from
the hybrid power system when climatic circumstances
change. In 2020 [13], Bilal Naji Alhasnawi and Basil H.
Jasim proposed distributed coordinated control for hybrid
M-grid, which might be used in both grid-connected and
islanded modes with hybrid energy supplies and changing
loads. The suggested system enables the coordinated
operation of distributed energy resources to provide active
power and extra service as needed. In addition, MPPT
approach has been used on both solar stations and wind
turbines. In 2020 [14], Bilal Naji Alhasnawi and Basil H ,
proposed an energy management system to satisfy the
demand, a hybrid system with distribution electric grid,
photovoltaic, and batteries was used as an energy source in
the consumer's home. In 2021 [15], Heesang Ko et al
presented a strategy for coordinating supervisory power. The
primary goal is to limit the penetration of additional
electricity from RERs into the grid, hence preventing
curtailments. To make it practical, the suggested approach is
Jasim & Jasim
used to create a grid-connected microgrid system that will
only run in response to demand changes and virtual power
plant (VPP) requests. In 2021 [16], K.Rayudu et al, presented
a mathematical model of a M-grid composed of a wind
power generation and PV system that are integrated into the
utility grid, and a PI Controller for controlling the transition
from grid-connected mode to island mode, with each DG
inverter set to constant current control mode to provide
preset power to the main grid. In an islanding situation, each
DG inverter is connected to voltage control mode when it
disconnects from the main grid. In 2021 [17], Nihad
Abdulkhudhur Jasim and Majli Nema Hawas proposed an
isolated DC M-grid, utilizing solar photovoltaic (PV) as the
RER source to deliver power to resistive DC charges, as well
as a hybrid energy storage system (HESS) for battery and
supercapacitor. To test this suggested technique for
managing the DC bus voltage, several situations of load and
solar insolation fluctuation are simulated. When the output
waveforms with and without HESS are examined, a
favorable decrease in transient voltage is found if the HESS
is used. In 2021 [18], Mehmet Emin Akdogan and Sara
Ahmed developed a modified reverse droop management
strategy in the Energy Storage System (ESS) to improve
three-phase PCC voltage quality in multi-microgrids
(MMG). In 2021 [19], Mathiesen, P. et al. developed a power
balancing technique for optimizing distributed energy
resource investments in the intra-hour fluctuation of solar
and demand of a home M-grid for building the M-grid
strategy. This strategy helps to limit the risks of intra-hour
proposed thorough design of the freestanding DC microgrid,
as well as the detailed design of the DC bus voltage
controller, which is the MPPT-based PI control algorithm
with DC bus voltage regulation. The Ziegler–Nichols
approach was used to fine-tune.
The present research's contributions can be summarized
in the following points:
? The dynamic operation of a M-grid consisting of
(PV, BESS, and loads) linked/unlinked to the utility
grid is studied and simulated.
? Grid-following mode, PQ control, and irradiance
fluctuation are studied.
? Grid-following, grid-forming procedure and a
resynchronization between them are performed.
? Maximum power point tracking from solar PV has
been achieved using Perturb and Observe (P & O)
algorithm and fuzzy logic techniques.
? Grid-forming mode and solar plant curtailment
have been carried out.
? Detection and diagnosis the faults types using the
discrete wavelet transform are performed.
? PQ control and imbalance (negative sequence)
correction are introduced as an ancillary services.
II. PROPOSED SYSTEM CONFIGURATION
The adopted electrical energy network is depicted in
Fig.1.