Candidate:
Hisham
Alharbi
Title:
Electricity
Market
Participation
and
Investment
Planning
Frameworks
for
Energy
Storage
Systems
Date:
July
6,
2020
Time:
9:30
AM
Place:
REMOTE
PARTICIPATION
Supervisor(s):
Bhattacharya,
Kankar
Abstract:
The
recent
trend
of
increasing
share
of
renewable
energy
sources
(RES)
in
the
generation
mix
has
necessitated
new
operational
and
planning
studies
because
of
the
high
degree
of
uncertainty
and
variability
of
these
sources.
RES
such
as
solar
photovoltaic
and
wind
generation
are
not
dispatchable,
and
when
there
is
excess
energy
supply
during
off-peak
hours,
RES
curtailment
is
required
to
maintain
the
demand-supply
balance.
Furthermore,
RES
are
intermittent
resources
which
have
introduced
new
challenges
to
the
provision
of
ancillary
services
that
are
critical
to
maintaining
the
operational
reliability
of
power
systems.
Energy
storage
systems
(ESS)
play
a
pivotal
role
in
facilitating
the
integration
of
RES
to
mitigate
the
aforementioned
issues.
Therefore,
there
is
a
growing
interest
in
recent
years
to
examine
the
potential
of
ESS
in
the
future
electricity
grids.
This
research
focuses
on
developing
market
participation
and
investment
planning
frameworks
for
ESS
considering
different
ownership
structures.
First,
a
novel
stochastic
planning
framework
is
proposed
to
determine
the
optimal
battery
energy
storage
system
(BESS)
capacity
and
year
of
installation
in
an
isolated
microgrid
using
a
novel
representation
of
the
BESS
energy
diagram.
The
proposed
models
are
developed
from
the
system
operator's
perspective
to
ensure
that
the
BESS
contributes
to
microgrid
operation
via
load
leveling
and
reserve
provisions
in
conjunction
with
the
spinning
reserve
from
dispatchable
distributed
generation
units.
A
decomposition-based
approach
is
proposed
to
solve
the
problem
of
stochastic
planning
of
BESS
under
uncertainty.
The
optimal
decisions
minimize
the
net
present
value
of
total
expected
costs
over
a
multi-year
horizon
considering
optimal
BESS
operation
using
a
novel
matrix
representing
BESS
energy
capacity
degradation.
The
proposed
approach
is
solved
in
two
stages
as
mixed
integer
linear
programming
(MILP)
problems
to
ensure
the
convergence.
The
optimal
ratings
of
the
BESS
are
determined
in
the
first
stage,
while
the
optimal
installation
year
is
determined
in
the
second
stage.
Extensive
studies
considering
four
types
of
BESS
technologies
for
deterministic,
Monte
Carlo
Simulations,
and
stochastic
cases
are
presented
to
demonstrate
the
effectiveness
of
the
proposed
approach.
The
thesis
further
studies
the
investment
decisions
on
BESS
installations
by
a
third-party
investor
in
a
microgrid.
The
optimal
BESS
power
rating,
energy
capacity,
and
the
year
of
installation
are
determined
while
maximizing
the
investor's
profit
and
simultaneously
minimizing
the
microgrid
operational
cost.
The
multi-objective
problem
is
solved
using
a
goal
programming
approach
with
a
weight
assigned
to
each
objective.
The
BESS
is
modeled
to
participate
in
energy
arbitrage
and
provisions
of
operating
reserves
to
the
microgrid,
considering
its
performance
parameters
and
capacity
degradation
over
the
planning
horizon.
Finally,
in
the
third
problem
addressed
in
the
thesis
in
the
context
of
electricity
markets,
the
non-strategic
and
strategic
participation
of
a
pumped
hydro
energy
storage
(PHES)
facility
in
day-ahead
energy
and
PBR
(regulation
capacity
and
mileage)
markets
are
examined.
The
PHES
is
modeled
with
the
capability
of
operating
in
hydraulic
short-circuit
(HSC)
mode
with
detailed
representation
of
its
operational
constraints,
and
integrated
with
an
energy-cum-PBR
market
clearing
model.
For
its
strategic
participation,
a
bi-level
market
framework
is
proposed
to
determine
the
optimal
offers
and
bids
of
the
PHES
that
maximize
its
profit.
The
operation
of
PHES
is
modeled
at
the
upper
level,
while
the
market
clearing
is
modeled
in
the
lower
level
problem.
The
bi-level
problem
is
formulated
as
a
mathematical
programming
with
equilibrium
constraints
(MPEC)
model,
which
is
linearized
and
solved
as
an
MILP
problem.
Several
case
studies
are
carried
out
to
demonstrate
the
impact
of
PHES'
non-strategic
and
strategic
operations
on
market
outcomes.
Furthermore,
stochastic
case
studies
are
conducted
to
determine
the
PHES
strategies
considering
the
uncertainty
of
the
net
demand
and
rivals'
price
and
quantity
offers.
Monday, July 6, 2020 9:30 am
-
9:30 am
EDT (GMT -04:00)