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Student Poster : Smart Loads for Voltage Control in Distribution Networks

Authors:
Smart Loads for Voltage Control in Distribution Networks
Zohaib Akhtar*, Balarko Chaudhuri, Ron Hui
2015 IEEE PES General Meeting
*Acknowledgement: Funded by the Commonwealth Scholarship.
A. STUDY SYSTEM
Low voltage (LV) side is modelled
in detail while the medium voltage
(MV) bus is considered to be
tightly regulated at 1.0 p.u.
Eight equally spaced single-phase
loads connected to each phase of
the LV feeder.
To simulate voltage disturbances,
a photovoltaic (PV) panel with a
peak power of 5.2 kW, and an
electric vehicle (EV) charging
facility of 3.0 kW are included at
each load terminal. Fig. 2: Segment of aLV distribution
network [2].
4. SIMULATION RESULTS
Fig. 1: (a) Smart load with reactive compensation (SLQ), (b) Smart load with
back-to-back converters (SLBC)
1. BACKGROUND
Increasing use of distributed generation (DGs) like rooftop photovoltaic
(PV) generation would cause over-voltage problem in low-voltage and/or
medium voltage (LV/MV) distribution networks
Charging the growing fleet of electric vehicles (EVs) during the night
could lead to under-voltage problem even during otherwise off-peak
hours
Such voltage problems could potentially become unacceptable with
increasing penetration of PVs/EVs
Reactive shunt compensators on their own are not very effective in
controlling the voltage at the LV level due to high R/X ratio of the system
2. RESEARCH OBJECTIVES
Validate the effectiveness of smart loads (SLs) [1] through system
studies in mitigating voltage problems caused by photovoltaic (PV)
generation and electric vehicle (EV) charging, using realistic low voltage
(LV) distribution network models
Estimating required SL ratings for effective voltage control
Comparison between different types of SLs in terms of compensator
rating, costs and performance under different system conditions
3. SMART LOAD (SL) TYPES
Fig. 3: Hourly variation in load, PV
output and EV charging power
A typical PV output profile is
generated using a half-hourly
average solar irradiation data.
The EV charging power is
assumed to be constant.
Over-voltage occurs during the
day time when the PV generation
is close to its peak value
Under-voltage occurs at EV
charging near peak load
50% loads are considered to be
non-critical
REFERENCES
[1] Z. Akhtar, B. Chaudhuri, and S. Y. R. Hui, “Primary frequency control
contribution from smart load with reactive compensation,” IEEE
Transactions
on Smart Grid, 2015
[2] “The impact of small scale embedded generation on the operating
parameters of distribution networks,” Department of Trade and Industry, UK,
Report, 2003.
6. FUTURE WORK
Design of an optimal control to minimize the control effort.
Load characterization and identification of loads that can serve as non-
critical loads.
Fig. 4: Variation of (a) supply voltage
at L8, (b) voltage across non-critical
load, (c) compensator voltage
magnitude and (d) phase angle over
24 hours
Fig. 5: Variation of (a) active and (b)
reactive power of smart load, (c)
active and (d) reactive power of the
compensator over a 24 hours
Fig. 7: Box plots for voltage across
(a)-(b) supply/mains, and (c)-(d)
noncritical loads for under-and
over-voltage events.
Fig. 6: Total reactive capacity of the
converters for SLQ and SLBC
expressed as a percentage of the
smart load (SL) rating
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5. CONCLUSION
Smart loads with back-to-back converters (SLBCs) can be used to
effectively control the voltage in aLV network.
SLBCs perform better compared to smart loads with reactive only
compensation (SLQs) especially, in case of over-voltage events caused
by photovoltaic (PV) generation.
While the performance of SLQs depend on the R/X ratio of the network,
SLBCs can ensure acceptable voltage regulation over a wider range of
R/X ratios.
Moreover, SLBCs can achieve better voltage regulation with less total
converter power capacity than SLQs. An SLBC would require one
additional power converter compared to an SLQ.
B. OVER- AND UNDER-VOLTAGE CONDITIONS
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