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synchronization problem, also called leaderless consensus, all agents synchronize to
a common value that is not prescribed or controllable. In tracking synchronization
problem, all agents synchronize to a leader node that acts as a command generator.
Neighboring agents can communicate with each other. The leader is only connected
to a small portion of the agents.
The secondary control of AC microgrids is similar to the tracking synchro-
nization problem of a multi-agent system where the DG voltages and frequencies
are required to track their nominal values. The dynamics of DGs in microgrids are
nonlinear and nonidenti cal. Therefore, input–output feedback lineariza tion is used
to transform the nonlinear heterogeneous dynamics of DGs to linear dynamics.
Input–output feedback linearization transforms the secondary voltage control to a
second-order tracking synchronization problem. The secondary frequency control is
transformed to a first-order synchronization problem using input–output feedback
linearization. Based on the transformed dynamics, fully distributed voltage and
frequency control p rotocols are derived for each DG. The proposed distributed
controls are implemented through a spars e communication network, with only
one-way communication links, where each DG requires its own information and the
information of its neighbors.
In AC microgrids, DGs can be of rotating machi nery or voltage source inverter
(VSI)-based types. The control structure of a VSI may vary based on the control
objectives such as voltage and frequency, or active and reactive powers. VCVSIs
have internal voltage and current controller loops that facilitate the voltage and
frequency contr ols of DG. However, in some DGs, the sole active and reactive
power control may be of interest. This requirement can be satisfied through the
current-controlled voltage source inverters (CCVSI). Up to this point, most of the
presented secondary control schemes have only covered the voltage and frequency
controls of VCVSIs. In this book, a two-layer control framework is introduced to
implement the secondary control for an islanded microgrid containing both VCVSIs
and CCVSIs. The first control layer deals with the voltage and freque ncy controls of
VCVSIs. Additionally, the active and reactive powers of VCVSIs are allocated
based on their active and reactive power ratings. The second control layer objec-
tives are to control the active and reactive powers of CCVSIs. Each control layer is
implemented through the distributed control of multi-agent systems.
The distributed secondary voltage control of AC microgrids can be made
adaptive with respect to the changes in the DG parameters and microgrid operating
conditions. The term adaptive refers to the following salient features of the pro-
posed controller. The proposed controller compensates for the nonlinear and
uncertain dynam ics of DGs and, hence, obviates the control design challenges
caused by the nonlinear dynam ics of DGs. The controller is fully independent of the
DG parameters and the speci fication of the connector by which each DG is con-
nected to the microgrid. Therefore, the controller can be deployed on any DG
regardless of the DG parameters and the connector specifications, and its perfor-
mance does not deteriorate by the change in DG parameters (e.g., due to aging and
thermal effects). The proposed controller appropriately responds to the changes in
the system operating condition, without any manual intervention, and adjusts the
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