Applied Engineering Sciences Deng (Ed.)
© 2015 Taylor & Francis Group, London, 978-1-138-02649-0
Optimal scheduling of LTC and switched shunt capacitors in smart grid
concer ning overnight charging of Plug-in Electric Vehicles
Sara Deilami, Amir S. Masoum, Mohammad A.S. Masoum, Ahmed Abu-Siada & Syed Islam
Department of Electrical and Computer Engineering, Curtin University, WA, Australia
ABSTRACT: It is well-known that load variation and nonlinearity have detrimental impacts on the operation
and performance of conventional power systems and future smart grids (SGs), including their voltage profiles,
power quality, losses, and efficiency, particularly during the peak load hours. This paper will illustrate the
performance of optimal scheduling of transformer Load Tap Changers (LTC) and Switched Shunt Capacitors
(SSCs) in Smar t Grids with nonlinear loads and Plug-in Electric Vehicle (PEV) charging activities to improve
voltage profile, reduce grid losses, and control the Total Harmonic Distortion (THD). An established genetic
algorithm (GA) for the dispatch of LTC/SSCs and a recently implemented algorithm, based on Maximum
Sensitivity Selections (MSS) optimization for the coordination of PEVs, are used to perform detailed simulations
and analyses.
Keywords: Smart grid, PEV coordination, charging, optimal dispatch, LTC and switched capacitors.
The changing nature of linear loads, harmonic cur-
rent injections of nonlinear loads and the intermit-
tent behavior of renewable distributed generation
(DG) systems have detrimental impacts on the oper-
ation and performance of the conventional aging
power network and the innovative smart g rids (SGs)
[1–3]. Examples of nonlinear loads are variable speed
drives, energy-efficient lights, switching converters,
smart appliances, and plug-in electric vehicles (PEVs).
Load variations change the balance and flow of active
and reactive power that can cause voltage regulation
problems while harmonic injections increase the total
harmonic distortion (THD), reduce efficiency, and
force premature aging of power systems components.
Possible solutions to solve the voltage and power
quality problems are the installation of passive, active,
and hybrid filters, as well as the utilization of custom
power devices which tend to be expensive alternatives
[2]. Recently, the possibility of rescheduling LTCs and
the existing Switched Shunt Capacitors (SSCs) to mit-
igate harmonic distortion in conventional power grids
have been proposed and implemented [1].
One of the main sources of load variation in SG
is random charging of PEVs, particularly during the
evening hours [4–6]. Two main approaches have been
proposed in the literature to prevent these problems:
i) consumers can be motivated to charge their vehicles
during the off-peak hours by offering price incentives
and implementing dynamic energy prices, ii) PEV
charging can be coordinated [5–7]. There are a num-
ber of offline and online PEV charging/discharge
coordination algorithms that are classified to decen-
tralize (distributed) and centralized strategies [5–7].
This paper will use the proposed genetic algorithm
(GA) of [1] to perform optimal scheduling of LTCs and
SSCs in Smart Grids with nonlinear loads and PEV
charging activities to improve voltage profiles, reduce
grid losses, and control THD. There charging PEV
scenarios are considered, simulated and compared:
i) uncoordinated (random), ii) the online maximum
sensitivities selection based coordination algorithm
(OL-MSSCA) of [7] and iii) an inexpensive overnight
MSS based coordination algorithm (ON-MSSCA).
Detailed simulations are presented and compared for
optimal GA scheduling of LTC/SSCs of a 449 node
SG network, populated with PEVs.
The LTC/SSCs scheduling problem is minimization of
energy loss over a 24-hour period [1]:
where P
is total power loss at hour t as a function of
(status of SSCs) and T
(LTC tap position), t =1
hour is the time inter val, while H , m, i and R
are the

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