Enrique
Mallada
Assistant
Professor
of
Electrical
and
Computer
Engineering
Johns
Hopkins
University
ABSTRACT
Implementing
frequency
response
using
grid-connected
inverters
is
one
of
the
popular
alternatives
to
mitigate
the
dynamic
degradation
experienced
in
low
inertia
power
systems.
However,
such
solution
faces
several
challenges
as
inverters
do
not
intrinsically
possess
the
natural
response
to
power
fluctuations
that
synchronous
generators
have.
Thus,
to
synthetically
generate
"virtual"
inertia,
inverters
need
to
take
frequency
measurements,
which
are
usually
noisy,
and
subsequently
make
changes
in
the
output
power,
which
is
therefore
delayed.
As
a
result,
it
is
not
a
priori
clear
the
whether
virtual
inertia
will
indeed
mitigate
the
degradation,
or
some
alternative
control
strategy
will
be
necessary.
In
this
talk,
we
present
a
comprehensive
analysis
and
design
framework
that
provides
the
tools
required
to
answer
this
question.
First,
we
develop
novel
stability
analysis
tools
for
power
systems,
which
allows
for
the
decentralized
design
of
inverter-based
controllers.
The
method
requires
that
each
inverter
satisfies
a
standard
H-infinity
design
requirement
that
depends
on
the
dynamics
of
the
components
and
inverters
at
each
bus,
and
the
aggregate
susceptance
of
the
transmission
lines
connected
to
it.
It
is
robust
to
network
and
delay
uncertainty,
and
when
no
network
information
is
available
reduces
to
the
standard
passivity
condition
for
stability.
Second,
by
selecting
relevant
performance
outputs
and
signal
norms,
we
define
system-wide
performance
metrics
that
explicitly
quantify
the
effect
of
frequency
measurements
noise
and
power
disturbances
on
the
overall
system
performance.
Using
a
novel
modal
decomposition,
we
derive
closed-form
expressions
for
system
performance
that
explicitly
capture
the
impact
of
network
topology,
generator
and
inverter
control
parameters,
and
machine
rating
heterogeneity.
Finally,
we
leverage
this
framework
to
design
a
new
dynamic
droop
control
(iDroop)
mechanism
for
grid-connected
inverters
that
exploits
classical
lead/lag
compensation
to
outperform
standard
droop
control
and
virtual
inertia
alternatives
in
both
joint
noise
and
disturbance
mitigation
and
delay
robustness.
BIOGRAPHY
Enrique
Mallada
is
an
Assistant
Professor
of
Electrical
and
Computer
Engineering
at
Johns
Hopkins
University.
Prior
to
joining
Hopkins
in
2016,
he
was
a
Post-Doctoral
Fellow
in
the
Center
for
the
Mathematics
of
Information
at
California
Institute
of
Technology
from
2014
to
2016.
He
received
his
Ingeniero
en
Telecomunicaciones
degree
from
Universidad
ORT,
Uruguay,
in
2005
and
his
Ph.D.
degree
in
Electrical
and
Computer
Engineering
with
a
minor
in
Applied
Mathematics
from
Cornell
University
in
2014.
Dr.
Mallada
was
awarded
the
ECE
Director’s
PhD
Thesis
Research
Award
for
his
dissertation
in
2014,
the
Cornell
University
Jacobs
Fellowship
in
2011
and
the
Organization
of
American
States
scholarship
from
2008
to
2010.
His
research
interests
lie
in
the
areas
of
control,
dynamical
systems
and
optimization,
with
applications
to
engineering
networks
such
as
power
systems
and
the
Internet.