Conference PaperPDF Available

Student Poster : Smart Loads for Voltage Control in Distribution Networks

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.
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].
Fig. 1: (a) Smart load with reactive compensation (SLQ), (b) Smart load with
back-to-back converters (SLBC)
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
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
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
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
[1] Z. Akhtar, B. Chaudhuri, and S. Y. R. Hui, “Primary frequency control
contribution from smart load with reactive compensation,” IEEE
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.
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
 
 
  
  
 
   
   
 
   
  
 
   
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.
... The basic structure of the smart load is shown in Fig. 1, where ES consists of converter #A and converter #B; VDC represents the DC voltage of ES; C represents the DC capacitor of ES; Lf and Cf are filter inductance and filter capacitance of ES output side respectively; VES represents the ES output voltage; ISL represents the branch current; VNCL represents the non-critical load voltage; VSL represents the smart load voltage. The proposal of smart load was originally for solving the voltage fluctuation problem after the integration of distributed generation [8]. However, as shown in Fig.1, due to the fact that the new type of ES adopts the back-to-back converter structure, the smart load also has the characteristics of power control now [9]. ...
Full-text available
In order to deal with the real-time power imbalance problem as the integration of renewable energy, and guide users to optimise power consumption, the real-time price technology has been gradually introduced into the demand management of distribution network. However, the response to real-time price is still highly dependent on the artificial switching on/off loads, the intelligent level of which needs to be improved urgently. To solve this problem, improve the response speed and response degree of loads, an intelligent real-time price responding method based on smart loads is proposed. First, the basic principles of smart loads are analysed. After that, the control strategy and control loop which can make smart loads realise the automatic response of real-time price are designed. At last, verified by the simulations conducted in MATLAB/Simulink, the real-time price responding method proposed here is reliable and effective, and the real-time price responding speed and responding degree of loads can be greatly improved.
Smart microgrid concept-based AC, DC, and hybrid-MG architecture is gaining popularity due to the excess use of distributed renewable energy generation (DRE). Looking at the population demand and necessity to reduce the burden, appropriate control methods, with suitable architecture, are considered as the developing research subject in this area. Previously, a huge volume of literature related to the control strategies of the microgrid (MG) architecture are discussed; however, a systematic and coordinated literature review of the hierarchical control methods based on different MG configuration are discussed very less. In this proposed approach, the control hierarchy of the MG system is divided into three sections as primary, secondary, and tertiary approaches. A brief literature review of the primary, secondary, and tertiary approaches is addressed for respective MG structures. In addition, the manuscript presents the highpoints of state-of-art control techniques with individual merits and demerits. Furthermore, the future trends in the MG control from the presented literature review are analyzed and related simulation study is also presented to provide an additional contribution in this field.
Full-text available
Frequency-dependent loads inherently contribute to primary frequency response. This paper describes additional contribution to primary frequency control based on voltage-dependent noncritical (NC) loads that can tolerate a wide variation of supply voltage. By using a series of reactive compensators to decouple the NC load from the mains to form a smart load (SL), the voltage, and hence the active power of the NC load, can be controlled to regulate the mains frequency. The scope of this paper focuses primarily on reactive compensators for which only the magnitude of the injected voltage could be controlled while maintaining the quadrature relationship between the current and voltage. New control guidelines are suggested. The effectiveness of the SLs in improving mains frequency regulation without considering frequency-dependent loads and with little relaxation in mains voltage tolerance is demonstrated in a case study on the IEEE 37 bus test distribution network. Sensitivity analysis is included to show the effectiveness and limitations of SLs for varying load power factors, proportion of SLs, and system strengths.