IEEE Electrification Magazine - December 2013 - 27

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economical operation of esss in
microgrids. a genetic algorithm optiFrequency
mization technique based on a multiobjective function was used to
evaluate the economic impact of the
Storage Power
energy-storage-specific costs on the
Voltage
net present value of energy-storage
installations in distribution substations. one research group proposed a
two-stage stochastic optimal algo1′ 30″
1′ 20″
1′ 10″
1′ 00″
0′ 50″
0′ 40″
0′ 30″
rithm for sizing the ess in an isolated wind-diesel power system. the Figure 8. The microgrid voltage, frequency, and output power of a storage inverter when
authors considered wind penetra- transitioning from island to grid-tie mode.
tion, ess efficiency, and diesel operating strategy to minimize the cost of
supplied energy. research in another
Frequency
work presented an integrated electricity production cost analysis for
Source 1
autonomous electrical networks
based on renewable energy sources
Voltage
and energy-storage configurations.
the initial cost of the energy storage,
Storage Power
the input electricity, and fuel cost, as
well as the fixed and variable mainte2′ 30″
2′ 00″
1′ 30″
1′ 00″
0′ 30″
0′ 00″
nance and operating costs of the
entire installation were taken into
consideration. a group of researchers Figure 9. The off-grid to on-grid transition with a storage inverter in voltage mode and a source
inverter in current mode.
made use of particle swarm optimization to achieve optimal dispatch of
controllable loads and generators as well as to effectively
all considered contingencies. a MoPso approach, which
use the battery storage of each microgrid. the cost of the
adopts differential evolution algorithm, was presented to
microgrid is reduced by selling the stored energy at higher
optimize the operation of an interconnected microgrid,
prices and shaving peak loads from the larger system. the
which comprises a variety of distributed energy resources
authors in another work focused on the optimal ess for
and storage devices to minimize both cost and emission
maximizing the support to the network voltage control in a
resulted from supplying local demands.
distributed system. it has been shown that the location of
energy-Storage Interface
the ess impacts the transient stability and voltage quality
and controls in a microgrid
of a multibus microgrid.
figure 5 shows a 500-kW energy-storage inverter and 250Multiobjective particle swarm optimization (MoPso)
kWh, 500-kW li-ion battery for the fort sill microgrid. the
has become an efficient tool for solving the multiobjective
inverter plays a critical role to regulate voltage and freoptimization problems in power system by searching for
quency and mange transitions to island and grid-tie
an acceptable pareto-optimal set. Xu and singh proposed
a modified particle swarm optimization based on multiobjective optimization algorithm to solve the
energy-storage design problem,
which not only considers energyStorage Power
storage capacity and power rate but
also the operation strategy. the
Renewable
authors in another work proposed a
Frequency
MoPso method to determine an
optimal static var compensator (sVc)
installation scheme for the required
0′ 25″
0′ 20″
0′ 15″
0′ 10″
0′ 05″
0′ 00″
loading margin with the sVc installation locations and capacities Figure 10. The microgrid frequency and output power of two inverters when transitioning from
derived from the use of the sVc for grid-tie to island mode.

IEEE Electrific ation Magazine / d ec em be r 2 0 1 3

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