Voltage Regulation of Electric Power Network Interconnected with Wind Energy
Distributed Generations
Abdellah Bouakra1, Fouad Slaoui-Hasnaoui2, Michella Rustom3, Semaan Georges4
1,2
Université du Québec en Abitibi-Témiscamingue, Québec, J9X 5E4, Rouyn-Noranda, Canada.
3,4
Notre Dame University Zouk Mosbeh, Lebanon.
1
2
abdellah.bouakra@uqat.ca; fouad.slaoui-hasnaoui@uqat.ca; 3mbrustom@ndu.edu.lb; 4sgeorges@ndu.edu.lb;
Abstract— The large scale connection of power generation
in distribution networks causes deregulation in power
system networks. This paper focuses on studying the
voltage changes at each node of the distribution network
before and after the insertion of wind turbines as power
generators, and also proposes two optimal voltage control
methods in order to maintain a stable voltage profile.
Results of the simulations are presented in order to
confirm the proposed ideas and assert the effectiveness of
the used regulators as well as their optimal capacity
control.
Index terms— Distributed Generation (DG), Distribution
network, Renewable Energy, Voltage control, Wind
turbine.
I. INTRODUCTION
In the recent years, the electrical system has undergone a
significant increase of energy producers connected to the
networks. However, current systems were not designed
effectively to accommodate these new productions.
Consequently, some important technical problems arise due to
the connection of a large volume of electric energy generators
to these networks, such as the constraints on the functioning
and operation of the network, the resulted impact on voltage
levels, the risk of congestion as well as the appearance of
reactive energy flow.
Nowadays, current researches mainly focus on the insertion of
energy producers in the distribution networks, such as wind
turbines. In this context, El-Khattam and al. [6] shows the
benefits of installing DG in order to generate power in the
distribution system and to enhance the distribution system’s
voltage profile and reduce the electric system losses. J. W.
Smith and al. have studied the impacts of connecting wind
energy turbines on the voltage profile [5], where the load flow
probabilistic method was used to analyze the effects on
voltage quality after the connection of wind turbines in the
distribution networks [11-16-17]. Dong Dong Li and al. have
used and applied the analytical methods in order to study the
effects of wind power on the reliability of distribution systems
[15]. J. Yang showed the stability effects of the static voltage
in response to the insertion of a wind power generator in a
radial distribution system.
Daeseok R., and al. [2] proposed a method based on statistical
analysis in the purpose of regulating the voltage after the
insertion of energy producers; whereas, Cortinas, D. and P.
Juston [3] proposed an optimal positioning of the generators in
the network which leads to an improvement in the voltage
profiles. Furthermore, Scott, N.C., and al. [7] used another
978-1-5090-4479-5/17/$31.00 ©2017 IEEE
approach based on controlling the wind load in order to
regulate the voltage. Bollen, M.H.J. and A. Sannino [10]
presented an algorithm for controlling the voltage using the
energy producers’ reactive power. Kondoh, J., and al. [12]
proposed two methods for voltage control: cooperative control
and independent control. Niknam, T., and al. [9] presented an
algorithm based on the genetic code for the voltage regulation
Volt/Var. The A.D.T., and al. [13] used the voltage regulation
controller (PI) in order to determine the generator maximum
power that must be injected in the network. Finally, Mahmud,
M. A., and al. [18] used the compensation approach of the
reactive power for the voltage control.
The aim of this article is to bridge the gap between the
different approaches and presents a generalized model of a
distribution network interconnected with a wind turbine as a
power generator in order to study the variable behavior of the
voltage as well as the optimal regulation techniques. Several
simulations
were
performed
using
the
platform
Matlab®/Simulink® in order to verify and validate the different
control models.
II. WIND TURBINE MATHEMATICAL MODEL
The wind turbine aerodynamics are represented by the
interaction between the wind and the wind rotor. This
aerodynamic characteristic is described by the disc theory [4]
as shown in Fig. 1. This theory is used to determine the
available power in the wind (Pv) for a specific disc swept by
the rotor (refer to surface a in Fig.1). This theory also
describes the relationship between this available power and
the power extracted from the rotor itself (Pt). The
instantaneous power (Pv) can be determined using the
following expression: [14]
1
(1)
=
2
Where ρ, the air density (kg/m3); v, the wind velocity (m/s); a,
the swept area by the rotor (blades) (m2). The wind turbine
power coefficient is also defined by the following formula:
=
(2)
Hence, the expression of the power extracted from the rotor
can be deduced as follows:
1
(3)
=
2
Where r, the wind turbine rotor radius (m).Then, the rotational
torque exerted by the wind on the turbine (or the mechanical
torque at the turbine outlet) is defined by:
387
=
(4)
Fig. 3. Simulink® model of a wind generator connected to the network
Fig. 1. Illustration of the disk theory
Fig. 2. Generalized power electronics converter for wind systems
Where Ω, the angular mechanical velocity of the turbine rotor
(rad/s). Note that all these quantities will be used for modeling
the wind turbine.
III. WIND TURBINE CONFIGURATION AND CONNECTION TO
THE ELECTRICAL NETWORK
There exist several configurations of wind turbine connection
in the electrical network. However, Fig. 2 illustrates the
typical configuration of a wind type generator that is
connected to the network. This configuration was used to
illustrate the work presented in this article. It consists of a
power converter back-to-back (rectifier/inverter) that provides
the best energy flow control as well as the best performance.
The bridge diode rectifier PWM corrects the voltage and
frequency variation of the wind generator and provides
excitation to the induction generator. The configuration of the
inverter is identical to that of the rectifier. It also supplies the
generated power to the grid. Fig. 3 shows the overall system of
the modeled wind turbine connected to the network via a
synchronous generator.
IV. IMPACTS STUDY OF THE ENERGY PRODUCTION ON THE
DISTRIBUTION NETWORKS
Energy production may cause some impacts on the power
system. These impacts can be classified into two groups: the
impacts on distribution and the impacts on transportation.
A. Modification of the Power Flow
The grid delivers electricity from the power producers plants,
mainly located on the transport network, to customers via the
distribution network. In this case, the electricity flow is
unidirectional. However, the presence of produced energy can
create bidirectional flows of active power within the
distribution networks; moreover, when the production exceeds
the consumption, ascending flows toward the transport
networks occur. This phenomenon is illustrated as shown in
Fig. 4.
However, changing the power flow can cause the change of
material existing on the distribution networks (measurement
devices, equipment protection, etc.) which are often
unidirectional. Furthermore, the power producer connection
can induce a reversal of power flow in the grid. Hence, they
become bidirectional. Therefore, this fact engenders problems
of incompatibility between the current network and the
presence of energy on it. The first consequence of these
bidirectional power flows is that it becomes necessary to
modify the protection plan of electrical networks. The energy
generators provide indeed the power of short-circuit
downstream protections, which have the potential effects of
the blind or the trigger inadvertently. The safety of people and
property may be at stake.
B. Impact on the Voltage Profile
The addition of one or more energy producers can easily
create one or more tension rises. These elevations can be
transformed into overvoltage and exceed the permissible
limits, especially in the case of light load on the network. A
single power generator connected to the node N is considered
in Fig. 5. The voltage drop between the source station and the
N connection point is given by the following expression:
QN
PN
∆ =
(5)
Where PN & QN the active and reactive power at node N
respectively; PG & QG the active and reactive power supplied
by the generator respectively; PL & QL the active and reactive
power consumption respectively; QC, the reactive power
compensation device.
388
Fig. 6. General Network Analysis
Fig. 4. Energy flow of a distribution network in the presence of DG
Fig. 7. Rural LV network simulated on Matlab®/Simulink® without
inserting DG
Fig. 5. Determination of the voltage drop on a line in the presence of
DG
Consider now the case of a general network consisting of N
nodes where N loads are connected as shown in Fig. 6. The
voltage drop between the source and the connection point Nj is
given by the following formula: [8]
∆
=
∑
∑
.
∑
∑
.
(6)
Where Usource, the upstream voltage of the short-circuit
impedance (R1, X1); Pj & Qj, the active and reactive power at
node Nj; n, the number of nodes; and j = 1, 2, ..n.
C. Simulation of Overvoltage Problem
The three-phase LV distribution network was modeled and
simulated using the platform Matlab®/Simulink® as shown in
Fig. 7. Equation 6 has been used to calculate the voltage drop
at each node. The network studied consists of 14 nodes, 10
loads (P and Q) supplied by a 160-kVA, 20/0.4-kV step-down
transformer. This type of network is depicted here because the
surge phenomenon is easily identified, and at this voltage
level, the linear resistance is highly more important than the
linear reactance (R≫X). For the study, the network was
divided into two zones: 1 and 2, where each zone represents a
distribution line. Hence, two different scenarios were
simulated, the first one without the insertion of the power
generator and the second scenario when it is connected.
1.
In the absence of the power generator, the network is
operating in a conventional configuration. Moreover, the
voltage drops from the source station toward to the farthest
point of consumption. It is noticeable that in both zones 1 and
2, the voltage reaches low values at the end of the line for the
case of full load (100%). However, these values recorded
remain in the voltage limit values along the whole network.
2.
Connection of the Power Generator
In the second scenario, two wind turbines are connected to
nodes 11 and 14 (zone 2) as shown in Fig. 9. The simulations
were carried out with the presence of two energy producers as
shown in Fig. 10.
It is easily seen that the energy producer connection (zone 2)
causes a significant increase in the voltage at the energy
producer connection point as well as at the neighboring nodes.
Furthermore, in the case of a partial load (50%), the voltage
reaches a critical level for the nodes 10, 11 & 14, surpassing
the permissible voltage limit. It should be noted that the
increase in the voltage depends on the power delivered by the
generator. Moreover, the relative difference increases linearly
after the energy producer connection; then, in the insertion
zone, this gap becomes a growing trend as one moves away
from the source station, which explains the appearance of
overvoltage on its profile.
Without the Power Generator:
The simulations were performed in order to calculate the
voltage drop at each node with two different load states 50%
and 100%. Fig. 8 illustrates the voltage profile when the
power generator is not connected to the network.
Fig. 8. Voltage profile for two load regimes without DG for zones 1 & 2
389
constant. In order to correct the output voltage of the generator
Vs, a Proportional-Integral-Derivative (PID) controller was
added to the excitation system.
Fig. 9. LV network simulated with two wind turbines connected to the
nodes 11 & 14
B. P/Q Model Simulations
The simulations were carried out on the network shown in Fig.
9 in the presence of the regulator P/Q. The tests done show
that the voltage regulation presents a good performance in
terms of precision and stability (Fig. 14, 15 & 16). The perfect
matching between the generator voltage and the excitation
voltage is obvious. The electrical powers also move in perfect
correspondence with the control voltage (Fig. 17). Hence, the
adapted control model P/Q allows obtaining two sets of
changes occurring at different instants: 1 & 1.2 s. At t = 1s, the
active power changes from 2.5 to 10.5 kW; while the reactive
power varies from a value of 1 to 4 kVAR at t = 1.2s.
Fig. 10. Voltage profile for two load regimes in the presence of DG for
zones 1 & 2
Fig. 12. Diagram AVR automatic voltage regulator [1]
V. P/Q MODEL AND CONTROL FOR A WIND GENERATOR TYPE
A. P/Q Model Presentation
P/Q Control allows to impose the active and reactive power
injected by energy producer in the connection node. Hence,
the input power set point is fixed directly at the output of the
synchronous generator. However, the reactive power control
loop imposes limitations on the synchronous generator as
shown in Fig. 11. The difference between the measured
reactive power and the reference power is translated into
control via the excitation voltage by a regulator (PI). This type
of control has been adapted by adding an Automatic Voltage
Regulator (AVR) as shown in Fig. 12; where VREF is the
reference voltage; Vt, the terminal voltage; and VStab, the
voltage stabilization.
Fig. 13. Regulation and stabilization of excitation system
Fig. 11. Control model (P/Q) of wind turbine connected to the network
In order to control and stabilize the excitation voltage of a
generator VFD, the diagram of Fig. 12 may be simplified (TC,
TC1, TB and TB1 can be neglected) as shown in Fig. 13; where
Vref is the reference voltage generator; Vt, the terminal voltage;
KA, the gain amplifier excitation system ST; KE, the gain
excitation system; KF, the gain compensation of system
excitation ST; TA, the amplifier time constant; TE, the system
excitation time constant; and TF, the compensator time
Fig. 14. Voltage profile with the control model (P/Q) for two wind
turbines
390
Fig. 15. Output Voltage Profile Vabc (pu)
Fig. 16. Excitation voltage profile Vf (pu)
Fig. 17. Power profile with the control model P/Q
The obtained results show that the control voltage is efficient
since the reference values have been well imposed on power
producers connecting node. Thus, during the production
change (at t = 1s), the active power is changing appropriately
with the dynamics of the modeled production. Moreover, this
change has a direct impact on the voltage profile.
VI. P/V MODEL AND CONTROL FOR A WIND GENERATOR TYPE
A. P/V Model Presentation
For this regulation type, a classical voltage control (AVR
type) for controlling the synchronous generator is used [1].
Hence, the modeling of the production system is achieved via
the limitations and the dynamics outlined earlier. The voltage
control is realized via the excitation voltage of the machine.
However, the overexcited or underexcited generator has the
effect of respectively increasing or decreasing the voltage
level at the connection node of the energy source.
B. P/V Model Simulations
Fig. 18 illustrates the power profile of the two wind turbines
connected to the grid. With this control, two set changes have
been obtained occurring respectively at different instants: 1 &
1.2 s. At t = 1s, the active power changes from 50 to 65 kW;
while the reactive power varies from 40 to 58 kVAR at t =
1.2s. The regulations obtained are effective, the reference
values are met and the disturbances have been eliminated.
Fig. 18. Power profile with the control model P/V
VII. CONCLUSION
This article discusses the impact of the integration of energy
generators in electrical distribution networks. The simulation
results show that the energy producer connection causes a
significant increase of the voltage at the connection point and
neighboring nodes. Moreover, in the case of a partial load, the
voltage reaches a critical level higher than the permitted
voltage. To solve this problem, two methods for voltage
control P/Q and P/V were combined with two controllers and
simulated on an interconnected network with a wind turbine.
The results accurately depict the optimum adjustability of
voltage of the two methods and their effectiveness in
maintaining the stability and the proper functioning of the
network.
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