IEEE Power & Energy Magazine - July/August 2021 - 35

the complexity, variety, and quantity of DERs integrated
into the distribution feeders. The grid of the future needs to
develop a comprehensive distribution network management
framework that unifies real-time voltage and frequency control
at the DER edge controller with network-wide energy
management at the utility-aggregator level.
Most of the existing test platforms are limited in terms of the
number of buses in the model and their applications. Therefore,
SCE has developed an in-house controller hardware-in-theloop
platform in the lab that is capable of modeling distribution
systems with many emulated DER controllers to simulate and
test new DER optimization algorithms. This platform can run
large power system models within a real-time simulation environment
with a synchronized time step of 1 s.
As detailed in Figure 9, the testbed uses DIgSILENT PowerFactory
software to model the quasi-dynamic behavior of a
distribution system with the associated controllers, such as volt/
var control, in conjunction with MATLAB/Simulink to implement
a central DER optimization algorithm. The platform has
been used for SCE's ongoing demonstration projects, including
the Network Optimized Distributed Energy System (NODES)
under the U.S. Department of Energy's Advanced Research
Projects Agency-Energy program. In the NODES project, the
distributed control architecture continuously monitors the operating
points of DERs and steers them toward optimal operating
solutions. It does this while dynamically procuring and dispatching
synthetic reserves based on the current system state
and forecasts of both ambient and load conditions. The control
algorithms invoke simple mathematical operations embedded
on low-cost microcontrollers that enable distributed decision
making on time scales that match the dynamics of distribution
systems with high renewable integration.
In this setup, a realistic feeder is modeled to be run by a transient
simulation synchronized by the system clock inside the
PowerFactory software. The engine can communicate through
OPC protocol to the external component. The model represents
the power system with dynamic transient details applied
for the whole distribution system assets, including photovoltaics
(PVs), batteries, capacitors, and loads. Advanced metering
infrastructure time-series data aggregated at the service transformer
level and DER generation time-series data are applied
for a 24-h simulation time. Also, several computational platforms
are used as physical DERs and communicate through a
network with the docker machine. The setup has been tested
for 500 aggregated points.
Figure 10 presents some results before and after running
the NODES optimization algorithm. In Figure 10(a) and (b),
the feeder-head active powers are presented for all three
phases. Figure 10(a) illustrates how the active power follows
the load and PV irradiance time-series data and causes
reverse power flow to the substation from 10 to 11 a.m., when
the irradiance is high. Figure 10(b) displays the same power
when the optimization steers the DER control to maintain the
voltage within the boundary and follow the reserve magnitude
target (RMT) signal with a specific pattern.
july/august 2021
Technically, the RMT is a setpoint for the feeder-head
active power, which can be defined by its boundaries and dispatched
to the central controller. As seen, some oscillation will
occur while pursuing the RMT signal and will settle down in a
short time after the RMT setpoint changes. Similarly, overvoltage
in several buses is portrayed in Figure 10(c) and (d). Before
optimization and running the optimization algorithm, the DER
reactive power contributes to maintaining the voltage under
the constraints for all nodes of the feeder.
Through this platform, SCE developed an innovative hardware
and software solution to integrate and coordinate DER
generation, distribution circuits, and end-use energy systems at
various points on the electric grid. Also, distributed control architecture
has been explored as an alternative solution for largescale
system control to manage the voltage and frequency in the
distribution system. The setup is flexible in providing alternative
grid management architectures that would enable an optimized
operation of numerous DERs in the grid. This platform will
enable real-time coordination between DERs, such as rooftop
and community solar assets and the grid, while proactively shaping
the electric load. This will alleviate the peak demand, reduce
the loadings and stress on the equipment, manage and maintain
the voltage, and harness the full potential of the DER on the grid,
leading to more efficient grid operation and promoting SCE's
vision for reimagining the grid of the future.
Flexibility in a More
Electrified California
Since transportation and its associated fossil fuel refinement
contribute to one-half of California's greenhouse gas
emissions, the electrification of cars, buses, and mediumand
heavy-duty trucks will have to increase significantly
to achieve carbon neutrality by 2045. Based on current car
ownership and usage patterns in California, 26 million passenger
vehicles, 900,000 medium-duty trucks, and 170,000
heavy-duty vehicles will need to be electric by 2045. This
will increase the electric load by nearly 130 TWh, representing
more than 33% of the grid-served load. Similarly,
almost 75% of building space and water heating will need
to be electrified, which will increase the electric load by
nearly 50 TWh, representing around 15% of the total 2045
grid load.
The electrification of buildings and transportation is
expected to account for almost one-half of the total grid
demand in 2045. The associated load is assumed to feature significant
flexibility, driven by more effective time-of-use rates
and control technologies that enable building automation and
smart EV charging strategies. Management of flexible load
through up to 10% of building loads and 50% of light-duty EV
charging is assumed in two high electrification scenarios: 1)
the balanced scenario, which focuses on both in-state and outof-state
resource development, including out-of-state transmission
development, and 2) the solar-heavy in-state scenario,
which does not exceed existing California independent system
operator import limits.
ieee power & energy magazine
35
IEEE Power & Energy Magazine - July/August 2021

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - July/August 2021
