IEEE Electrification Magazine - December 2013 - 28

modes. the inverter control is designed for the device to
operate in voltage mode (grid forming).
in voltage mode, the inverter behaves as a synchronous
generator and regulates its output voltage magnitude and
phase to adjust its output reactive
and active power. it can serve as a frequency and voltage reference for
other sources in a microgrid. Voltage
mode is against current mode, in
which the inverter behaves as a current source and adjusts its real and
reactive power by varying the phase
and magnitude of output voltage.
a typical control block diagram for
a microgrid storage inverter is shown
in figure 6. this control can operate
the inverter in both island and gridtie modes and support the transition
mechanism. during island mode, if
the storage is the sole source, it
needs to provide power to all loads.
Voltage magnitude is only adjusted
in this mode. When the storage is
working in parallel with other sources, it adjusts the terminal voltage
phase to change the output power
and regulate frequency. the feedback
for angle adjustment can come from both output power
and system frequency. the feedback for terminal voltage
magnitude adjustment can come from both output reactive power and system voltage.
When the microgrid is in grid-tie mode, the frequency
is determined by the grid. the inverter regulates the phase
of output voltage versus grid to adjust output power. it
should be noted that this control can place the storage in
either charging or discharging mode in both island and
grid-tie modes. it means that the direction of the power
can be both ways while the inverter is in voltage mode.
adjustment of terminal voltage magnitude versus grid
voltage regulates the reactive power.
figures 7-10 show the traces for a microgrid system
with an energy-storage inverter, two inverter-based sources, and loads. the energy-storage inverter is in voltage
mode, and the inverter-based sources are in current mode.
figure 7 shows the system voltage and frequency as well
as the total power delivered by the inverters when all
three inverters are running in off-grid mode. the system
starts from zero voltage and experiences step load changes. the load is initially at 40 kW and then is reduced to
12.5 kW and zero in steps. the system voltage and frequency experience small variations according to the block
diagram of figure 6.
figure 8 shows the waveforms of the voltage, frequency, and output power of the storage inverter when the system is moved from off-grid to grid-tie mode. the inverter
settings are different for these two modes depending on

the battery's state of charge and system load. in off-grid
mode, the inverter is providing 10 kW because of the load
demand. in grid-tie mode, the inverter is charging the
storage with 20 kW by power settings.
another example illustrating the
off- to on-grid transition is shown in
figure 9. initially, the storage inverter is
configured as black start supporting
the system's voltage and picks up 20
kW of load. one inverter-based source
is configured in current mode and follows the storage inverter's power command, so that each one shares 10 kW.
at 85 s, the microgrid is reconnected to
the grid. the source inverter and storage inverter follow their power command of 0 and 20 kW of charging,
respectively.
figure 10 shows the waveforms of
the voltage, frequency, and output
power of two inverters when the system transitions from grid-tie to offgrid mode. source inverter 1 is in
current mode, and its output power
remains constant during both modes.
the storage inverter is in voltage
mode, and its power changes from 15
to 35 kW. during the transition, the frequency drops to
59.35 Hz before recovering to 59.85 Hz in island mode.

Multiobjective
particle swarm
optimization has
become an efficient
tool for solving the
multiobjective
optimization
problems in power
system by searching
for an acceptable
pareto-optimal set.

I E E E E l e c t r i f i c ati o n M agaz ine / december 2013

For Further reading
c. Marnay, H. asano, s. Papathanassiou, and g. strbac, "Policymaking for microgrids," IEEE Power Energy Mag., vol. 6,
no. 3, pp. 66-77, 2008.
M. d. Johnson and r. a. ducey, "overview of u.s. army
microgrid efforts at fixed installations," in Proc. IEEE
Power and Energy Society General Meeting, 2011, pp. 1-2.
(2012, oct. 15). u.s. army installation Management
energy Portfolio. [online]. available: http://armyenergy.hqda.
pentagon.mil/docs/energy_Portfolio_15_sep_10.pdf
Q. fu, l. f. Montoya, a. solanki, a. Nasiri, V. bhavaraju, t.
abdallah, and d. c. Yu, "Microgrid generation capacity
design with renewable and energy storage addressing
power quality and surety," IEEE Trans. Smart Grid, vol. 3,
no. 4, pp. 2019-2027, dec. 2012.
M. Nick, M. Hohmann, r. cherkaoui, and M. Paolone,
"on the optimal placement of distributed storage systems
for voltage control in active distribution networks," in Proc.

2012 3rd IEEE PES Int. Conf. Exhibition on Innovative
Smart Grid Technologies, 2012, pp. 1-6.
c. chen, s. duan, t. cai, b. liu, and g. Hu, "optimal allocation and economic analysis of energy storage system in
microgrids," IEEE Trans. Power Electron., vol. 26, no. 10,
pp. 2762-2773, oct. 2011.
Jason stamp, "sPiders: smart power infrastructure
demonstration for energy, reliability, and security," in

http://www.armyenergy.hqda http://www.pentagon.mil/docs/energy_Portfolio_15_sep_10.pdf

Table of Contents for the Digital Edition of IEEE Electrification Magazine - December 2013