IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 2, APRIL 2015
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Comparison of Detailed Modeling Techniques for
MMC Employed on VSC-HVDC Schemes
Antony Beddard, Student Member, IEEE, Mike Barnes, Senior Member, IEEE, and Robin Preece, Member, IEEE
Abstract—Modular multilevel converters (MMC) are presently
the converter topology of choice for voltage-source converter
high-voltage direct-current (VSC-HVDC) transmission schemes
due to their very high efficiency. These converters are complex,
yet fast and detailed electromagnetic transients simulation models
are necessary for the research and development of these transmission schemes. Excellent work has been done in this area, though
little objective comparison of the models proposed has yet been
undertaken. This paper compares for the first time, the three
leading techniques for producing detailed MMC VSC-HVDC
models in terms of their accuracy and simulation speed for several typical simulation cases. In addition, an improved model is
proposed which further improves the computational efficiency of
one method. This paper concludes by presenting evidence-based
recommendations for which detailed models are most suitable for
which particular studies.
Index Terms—Accelerated model, electromagnetic-transient
(EMT) simulation, HVDC transmission, modular multilevel converter (MMC), voltage-source converter (VSC).
I. INTRODUCTION
T
HE DEMAND for voltage-source converter (VSC) highvoltage direct-current (HVDC) transmission schemes has
grown significantly in recent years. This growth is primarily
due to the improvements in the voltage and power ratings of
insulated-gate bipolar transistors (IGBTs) and a number of new
VSC-HVDC applications, such as the connection of large offshore windfarms.
Since its inception in 1997 and until 2010, all VSC-HVDC
schemes employed two- or three-level VSCs [1]. In 2010, the
Trans Bay Cable Project became the first VSC-HVDC scheme
to use modular multilevel converter (MMC) technology.
The MMC has numerous benefits in comparison to two- or
three-level VSCs; chief among these is reduced converter
losses. Today, the three largest HVDC manufacturers offer a
VSC-HVDC solution which is based on multilevel converter
technology.
Manuscript received August 12, 2013; revised December 14, 2013 and March
12, 2014; accepted April 29, 2014. Date of publication June 09, 2014; date of
current version March 20, 2015. This work was supported by the Engineering
and Physical Sciences Research Council (EPSRC) under Grant EP/H018662/1Supergen ‘Wind Energy Technologies’. Paper no. TPWRD-00903-2013.
The authors are with the School of Electrical and Electronic Engineering,
University of Manchester, Manchester M13 9PL, U.K. (e-mail: antony.
beddard@postgrad.manchester.ac.uk; mike.barnes@manchester.ac.uk).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TPWRD.2014.2325065
Modelling MMCs in electromagnetic transient simulation
(EMT) programs presents a significant challenge in comparison
to modeling a two- or three-level VSC. The stack of series
connected IGBT's in each arm of a two- or three-level VSC is
switched at the same time. This simultaneous switching action
enables the stack of IGBTs to be modeled as a single IGBT for
many studies. The MMC topology, however, does not contain
stacks of series-connected IGBT's which have identical firing
signals and, therefore, comparable simplification in the model
cannot be made.
The converter employed on the Trans Bay Cable Project is
an MMC with approximately 201 levels. A traditional detailed
model (TDM) of this converter would require more than 2400
IGBTs with antiparallel diodes and more than 1200 capacitors
to be built and electrically connected in the simulation package's
graphical user interface, resulting in a large admittance matrix.
The admittance matrix must be inverted each switching cycle,
for which MMCs can have hundreds of times per fundamental
cycle which is extremely computationally intensive. This makes
modeling MMCs for HVDC schemes using traditional modeling techniques impracticable.
To address this problem, an efficient model was proposed by
Udana and Gole in [2], which is referred to as the detailed equivalent model (DEM) in this paper. In [2], the DEM was shown
to significantly reduce the simulation time in comparison with a
TDM without compromising accuracy. A drawback of the DEM
is that the individual converter components are invisible to the
user. This makes the model unsuitable for studies which require
access to the individual converter components and it makes it
difficult to reconfigure the converter submodule for different
topologies. Only one other publication has compared the DEM
with the TDM, which was performed in EMTP-RV [3].
A new model, referred to as the accelerated model (AM) was
proposed by Xu et al. in [4]. This model was found to offer
greater computational efficiency than a TDM without compromising accuracy and it gives the user access to the individual
converter components. In [4], an attempt was made to compare the AM simulation time with the DEM simulation time
data from [2]; however, a full and objective comparison could
not be completed because the models were built by different researchers on different computers.
The objective of this paper is to perform a much needed independent comparison of the TDM, DEM, and AM models which
will enable the reader to make a more informed decision when
selecting which type of detailed MMC model to use and to
have a greater degree of confidence in the MMC models' performance. In this paper, the TDM, DEM, and AM models are
built in the same software on the same computer and compared
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Equation (5) shows that the converter phase voltages are effectively controlled by varying the upper and lower arm voltages. Each converter arm contains a number of SMs: . The
SM capacitor voltage can be described by (6), assuming the SM
capacitance is sufficiently large enough to neglect ripple voltage
and that the capacitor voltages are well balanced
(6)
Fig. 1. Three-phase MMC.
in terms of their accuracy and simulation speed. This enables a
fair comparison between the DEM and the AM and it provides
the first independent verification for the AM against the TDM,
and the DEM against the TDM in PSCAD. Having completed
this verification, this paper also highlights potential limitations
of the AM and proposes an enhanced accelerated model (EAM)
with improved simulation speed.
The voltage produced by a converter arm is equal to the
number of SMs in the arm which are turned on, multiplied
by the submodule capacitor voltage as given by (7) and (8).
Through appropriate control of the SMs, the output voltage
magnitude and phase can be controlled independently. The
number of voltage levels that an MMC can produce at its output
is equal to the number of SMs in a single arm plus one
(7)
(8)
III. DETAILED MMC MODELING TECHNIQUES
II. MMC VSC-HVDC
The basic structure of an MMC is shown in Fig. 1. Each leg
of the converter consists of two converter arms which contain a
number of submodules, SMs, and a reactor
, connected in
series. The SM contains a two-level half-bridge converter with
two IGBT's and a parallel capacitor. The SM is also equipped
with a bypass switch to remove the SM from the circuit in the
event that an IGBT fails and a thyristor to protect the lower
diode from overcurrent in the case of a dc-side fault. The bypass switch and thyristor are, however, typically omitted from
steady-state and transient studies.
The SM terminal voltage
is effectively equal to the SM
capacitor voltage
when the upper IGBT is switched-on and
the lower IGBT is switched-off; the capacitor will charge or
discharge depending upon the arm current direction. With the
upper IGBT switched off, and the lower IGBT switched on, the
SM capacitor is bypassed and, hence,
is effectively 0 V.
Each arm in the converter, therefore, acts like a controllable
voltage source with the smallest voltage change being equal to
the SM capacitor voltage.
With reference to Fig. 1, the following equation for the phase
a converter voltage can be derived:
(1)
(2)
The converter arm currents consist of three main components
is due to the
as given by (3) and (4). The circulating current
unequal dc voltages generated by the three converter legs. Substituting (3) and (4) into (1) and (2), then summing the resulting
equations gives
(3)
(4)
(5)
This section describes three detailed modelling techniques
which represent the converter's IGBTs and diodes using a simple
two-state resistance.
A. Traditional Detailed Model
In a traditional detailed MMC model, each SM's IGBTs,
diodes, and capacitors are built in the simulation package
graphical user interface, and electrical connections are made
between the SMs in each arm as shown in Fig. 1. This is the
standard way of building a detailed MMC model and, hence, is
why this type of model is referred to as the traditional detailed
model (TDM). This method of modeling is intuitive and gives
the user access to the individual components in each SM;
however, for MMCs with a large number of SMs, this method
is very computationally inefficient.
B. Detailed Equivalent Model
The DEM uses the method of nested fast and simultaneous
solution (NFSS) [5]. The NFSS approach partitions the network into small subnetworks, and solves the admittance matrix for each network separately [2]. Although this increases the
number of steps to the solution, the size of admittance matrices
is smaller, which can lead to reduced simulation time. A summary of the DEM is presented in the Appendix; however, further information can be found in [2]. The DEM employed in this
comparison was obtained directly from PSCAD.
C. Accelerated Model
The accelerated model (AM) was proposed by Xu et al. in
[4]. In many respects, the AM is a hybrid between the TDM
and the DEM. The user is able to access the SM components,
as they can with the TDM, but the converter arm is modeled as
a controllable voltage source, which is similar to the DEM. An
overview of the AM is presented here; the reader is referred to
[4] for further information.
In the AM, the series-connected SMs are removed from each
converter arm, separated and driven by a current source with
BEDDARD et al.: COMPARISON OF DETAILED MODELLING TECHNIQUES
581
Fig. 3. Basic simulation model structure.
A. Model Structure
Fig. 2. Implementation steps for the accelerated model.
. A controllable voltage
a value equal to the arm current
source is installed in place of the SMs as shown in Fig. 2, where
the value of the controllable voltage source is given by
(9)
The AM reduces the size of the main network admittance
matrix by solving the admittance matrix for each SM separately.
The AM has two key advantages in comparison to the DEM.
The first is that the AM allows the user access to SM components. The second is that because the AM is implemented
using standard PSCAD components, the internal structure of
the SM can be easily modified; for example, changing from a
half-bridge SM to a full-bridge SM.
IV. SIMULATION MODELS
A detailed MMC model for a typical VSC-HVDC scheme,
employing the traditional detailed model (TDM) converter arm
representation, has been developed. This model is used as the
TDM simulation model base case. The simulation models for
the DEM and for the accelerated model (AM) are identical to
the TDM, except that the TDM converter arms are replaced with
the converter arms required for the DEM and AM, respectively.
This approach ensures that fair comparisons between the different modeling techniques can be made.
This model is similar in scope to [2] and [4] but represents
a subsection of the network rather than just the converter used
in [4]. This gives a more realistic timing comparison since one
would not normally just be simulating the converter in typical power system studies. The basic structure of the simulation
model and the key parameters are shown in Fig. 3.
Developing a TDM for an MMC with hundreds of SMs, such
as a commercial installation, would result in lengthy simulation
times. A 31-level MMC was selected for this model since it produces acceptable harmonic performance (
at the PCC) [6] with a nearest level controller (NLC) without unnecessarily increasing the simulation time and yet still providing
a sufficient converter complexity to provide a fair test. The key
factor which determines the required number of SMs in commercial HVDC installations is the dc voltage and the maximum
permissible voltage stress per IGBT, rather than the harmonic
content of the output waveform. Therefore, more levels would
be used in commercial installations.
The selection of the SM capacitance value is a tradeoff between the capacitance ripple voltage and the size of the capacitor. The SM capacitance was calculated to give a ripple voltage
of 10%.
The arm reactors have two main functions. The first function is to suppress the circulating currents between the legs of
the converter, which exist because the dc voltages generated by
each converter leg are not exactly equal. The second function of
the arm reactor is to limit the fault current rate of rise to within
acceptable levels. According to [7], the Siemens HVDC Plus
MMC arm reactors limit the fault current to tens of amperes per
microsecond even for the most critical fault conditions. The arm
reactor for this model was dimensioned to ensure that the fault
current rate of rise does not exceed 20 A s for a short circuit
between the dc terminals of the converter, and to limit the circulating current to approximately 0.15 p.u.
The dc system is modeled as a dc voltage source connected in
series with a frequency-dependent phase cable model (FDPCM)
which represents two 300-kV 100-km XLPE cables. The ac
network is modelled as a voltage source connected in series with
a resistor and an inductor, to give a relatively strong short-circuit
ratio (SCR) of 3.5. The converter transformer employs a delta/
star winding with a tap changer.
B. MMC VSC-HVDC Control Systems
A simplified diagram for the three-phase 31-level MMC control system is shown in Fig. 4.
1) Current Controller: The impedance between the internal
and the ac system voltage
voltage control variables
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IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 2, APRIL 2015
Fig. 7. Implementation of CCSC.
Fig. 4. Simplified MMC control system.
controllers are used to set the
and
real and reactive power, respectively
Fig. 5. MMC phase a connection to an ac system.
values to control the
(13)
(14)
Fig. 6. Implementation of the
3) Circulating Current Suppressing Controller: The circulating current is a negative-sequence (a-c-b) current at double
the fundamental frequency [8]. This current is found to increase
the rms value of the arm current leading to increased converter losses [8]. The circulating current suppressing controller
(CCSC) is able to suppress the circulating current by controlling the voltage across the arm impedance. The development
of this controller is based on work carried out in [8]. Using
phase a, as an example, the dc voltage can be described by (15).
Substituting (3) and (4) into (15) and then rearranging gives
current controller.
is shown in Fig. 5. Equation (10) describes the relationship between the internal voltage control variable and the
ac system voltage for the three phases
(10)
(16)
where
(17)
(18)
where
(11)
Equation (10) in the
where
(15)
In matrix form, (16) for the three phases can be written as
(19). Applying the
transform to (19) gives (20). The
zero-sequence quantities do not affect the -axis and -axis
values and, hence, the use of
in
synchronous reference frame gives (12),
(19)
(12)
The current controller employed in this model is a fast feedback
decoupled controller, which produces a voltage reference for the MMC based upon the current setpoint from the
outer controllers. The implementation of the controller is shown
in Fig. 6.
syn2) Outer Controllers: In the magnitude invariant
chronous reference frame with the -axis aligned with
, the
real and reactive power flow at the point of common coupling
can be described by (13) and (14), respectively. Feedforward
(20)
decoupled circulating current controller is employed with
A
reference values set to zero as shown in Fig. 7.
the
4) Capacitor Balancing Controller: The capacitor balancing
controller (CBC) ensures that the energy variation in each
converter arm is shared equally between the submodules within
that arm. The CBC method proposed in [9] has formed the basis
of many of capacitor balancing controllers for VSC–HVDC
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TABLE I
NORMALIZED MEAN ABSOLUTE ERROR FOR THE DEM AND AM WAVEFORMS
WHEN OPERATING IN STEADY STATE AT 1000 MW
TABLE II
NORMALIZED MEAN ABSOLUTE ERROR FOR THE DEM AND AM WAVEFORMS
WHEN OPERATING IN STEADY STATE AT 500 MW
Fig. 8. Steady-state simulation results for the three models. From top to
bottom: (a) Phase A output voltage. (b) Phase A output current. (c) Phase C
lower arm current. (d) Phase A upper arm mean capacitor voltage.
MMCs [2], [10]–[12]. The CBC employed here is also based
on this method.
5) Nearest Level Controller: A number of modulation
methods have been proposed for MMCs [9], [11], [12]. The
nearest level controller (NLC) method produces waveforms
with an acceptable amount of harmonic content when a suitable
number of MMC levels are employed. It is the least computational complex method of the aforementioned techniques and,
thus, is used for the model in this paper.
V. RESULTS
In this section, the three models are compared in terms of their
accuracy and simulation speed.
A. Accuracy
The models' accuracy is assessed for steady-state and transient events through conducting a range of typical studies. Their
accuracy is evaluated graphically and numerically by calculating the mean absolute error (MAE) of the waveforms produced by the DEM and AM with respect to the TDM. The MAE
is normalized to the mean value of the TDM waveform.
1) Steady-State: The steady-state waveforms produced by
the models for the converter operating as an inverter at 1000
MW are shown in Fig. 8. The waveforms are virtually identical
and this is confirmed by the very small ( 1%) normalized MAE
values given in Table I. The models were re-simulated for the
converter operating as an inverter at 500 MW and 100 MW, and
their normalized MAE values are given in Tables II and III, respectively. The results generally show that the accuracy of the
TABLE III
NORMALIZED MEAN ABSOLUTE ERROR FOR THE DEM AND AM WAVEFORMS
WHEN OPERATING IN STEADY STATE AT 100 MW
models decreases as the operating point decreases. This is especially the case for the phase current and arm current. At lower
operating points, the magnitude of the arm and phase currents
are smaller and the switching noise is more noticeable. It appears to be the case that the effect of this switching noise on the
dominant signal and the model's inability to replicate it is impacting the normalized MAE values. The average THD of the
phase A output voltages for the three models, when operating at
1000 MW in steady state, was found to be between 1.35% and
1.36%.
2) DC-Side Line-to-Line Fault: A dc line-to-line fault is applied at 4.5 s to the MMC terminals as shown in Fig. 3. The
dc circuit breakers (DCCBs) are opened 2 ms after the fault is
applied so that the dc voltage sources do not continue to contribute to the fault current. The MMC converter is blocked at
4.502 s, and the ac-side circuit breakers (CBs) are opened at
4.56 s. In this paper, the converter is considered to be blocked
when both IGBTs are switched off. The waveforms produced
by the models are shown in Fig. 9 and their normalized MAE
values are given in Table IV. The waveforms produced by the
DEM and the AM are virtually identical ( 1%) and very similar
( 2.5%) to the TDM, respectively. An error in the AM model's
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Fig. 9. DC line current for a dc line-to-line fault applied at 4.5 s. From top
to bottom: (a) dc current, (b) phase A output voltage, (c) phase A upper arm
current, and (d) phase A upper arm mean capacitor voltage.
TABLE IV
NORMALIZED MEAN ABSOLUTE ERROR FOR THE DEM AND AM WAVEFORMS
FOR A DC LINE-TO-LINE FAULT
phase voltage is shown in Fig. 9 at the instances when the arm
current goes through zero. This issue occurs because the AM
is not able to correctly determine the ON/OFF status of the SM
diodes in a single time step when the converter is blocked. This
issue is discussed further in Section V-A-4.
3) AC Line-to-Ground Fault: A line-to-ground fault is applied to phase A at the point of common coupling (PCC) for 60
ms at 4.5 s as shown in Fig. 3. The waveforms produced by the
models are shown in Fig. 10, and their normalized MAE values
are given in Table V.
With the exception of the Phase A upper arm current, the
waveforms produced by the DEM and the AM are virtually
identical ( 1%) and very similar ( 2.5%) to the TDM, respectively. From all of the simulations conducted, the greatest difference between the three models was found to be in the Phase
A upper arm current a few cycles after the fault is cleared when
the MMC becomes overmodulated as highlighted in Fig. 10(d).
This difference lasts for a few cycles, and there is no significant
difference in the peak current values for the three models.
IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 2, APRIL 2015
Fig. 10. Line-to-ground fault for the phase applied at 4.5 s. (a) Phase A output
voltage. (b) Phase A output current. (c) Phase A upper arm current. (d) Phase A
arm current, zoomed.
TABLE V
NORMALIZED MEAN ABSOLUTE ERROR FOR THE DEM AND AM WAVEFORMS
FOR A LINE-TO-GROUND AC FAULT
The circulating current is a key component of the arm current
as described in (3). Comparing the accuracy of the arm current
therefore effectively compares the models' ability to simulate
the circulating currents. The CCSC suppresses the circulating
currents to very low values in steady-state operation, which is
shown in Fig. 10(c) by the low levels of distortion in the arm
current waveforms before the ac fault and several cycles after it
are cleared ( 4.7 s).
4) AM Simulation Limitation: The AM implemented in this
paper was found to be unable to fully manage the simulation
case when the converter is blocked as shown in Fig. 9. To further demonstrate this issue, the converter is blocked at 3 s when
operating as an inverter at 1000 MW, and the Phase A output
voltage for the three models is shown in Fig. 11. Clearly, the
converter voltage for phase A for the AM is different.
This is an inherent issue with the implementation of the AM
and can be illustrated further at the SM level. A circuit diagram
for a blocked SM connected to a voltage through a resistor is
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TABLE VI
COMPARISON OF RUN TIMES FOR THE THREE MODELS FOR 5-s SIMULATION
Fig. 11. Phase A output voltage.
Fig. 12. Example SM test circuit.
Fig. 14. Simulation times of the three models for different MMC levels.
B. Simulation Speed
Fig. 13. Implementation of the SM test circuit based on AM principles.
shown in Fig. 12. A model of this circuit based on the principles
of the AM is shown in Fig. 13.
is measured in the primary circuit and
The SM current
is used as the current source reference in the secondary circuit,
and the SM voltage is measured in the secondary circuit and
is used as the voltage-source reference in the primary circuit.
Each network is therefore solved at the present time step based
on information from the other network at the previous time step.
Upon model initialization,
0 V and, therefore, the SM
current flows in the positive direction causing the upper diode
D1 to conduct and the SM capacitor to charge. Once the SM capacitor is fully charged, if the voltage-source value is reduced,
the upper SM diode
should become reversed biased. Assuming that the SM diodes are ideal, the SM capacitor voltage
should remain constant
and
0. However, this is
not the case with the model implemented based on the AM principles. The arm current in the primary circuit becomes negative
because the value of
is equal to
which is higher than
. At the next time step, the negative arm current value causes
the lower diode in the secondary circuit to conduct and, hence,
0. At the next time step, the arm current becomes equal
to
, causing the SM capacitor to charge. This behavior
continues for the remaining simulation time. This limitation is
understood to have been addressed by Xu et al. and is therefore
not discussed further in this paper.
A 5-s simulation was performed for a 16-, 31-, and 61-level
MMC using the three modeling techniques with a 20- s time
step. The simulations were conducted on a Microsoft windows 7
operating system with a 2.5-GHz Intel core iq7-2860 processor
and 8 GB of RAM, running on PSCAD X4. The simulation
times are given in Table VI and compared in Fig. 14.
The data show that the DEM is the fastest, and that TDM is
the slowest. It also shows that the simulation time for the TDM
increases at a much faster rate than the DEM and AM models
as the number of converter levels increases.
It is worth noting that the results in [2] and [4] do appear, in
general, to show that their respective models simulate faster in
comparison to the TDM than the results presented in Table VI.
The models simulated in this report are, however, different from
the models employed in [2] and [4] in terms of complexity
which may explain the difference.
1) Enhanced AM Model: The AM has the advantage that it
is much faster than the TDM without noticeably sacrificing accuracy for the majority of case studies. It does, however, need to
be used with care when the converter is blocked. In comparison
with the DEM, the AM has the advantage of allowing access
to the SM components, but it is slower. This paper proposes an
enhancement to the AM to improve its speed.
The procedure outlined in [4], to produce the AM divides
the series-connected SMs in each arm into individual circuits,
driven by a current source whose value is equal to the arm
current, as explained in Section III-C. This approach effectively
creates a subsystem for each SM and solves the admittance
matrix for each SM separately. Although this increases the
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IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 2, APRIL 2015
TABLE VII
COMPARISON OF RUN TIMES FOR DIFFERENT AM MODELS
Fig. 15. Line-to-ground fault for phase A applied at 4.5 s.
TABLE VIII
NORMALIZED MEAN ABSOLUTE ERROR FOR THE AM AND AM30 WAVEFORMS
FOR A LINE-TO-GROUND AC FAULT
number of steps to the solution, the size of admittance matrices
is smaller, which can lead to reduced simulation time [2], [4],
[5] as shown in Table VI.
The simulation speed is affected by the number of steps to the
solution and the size of the admittance matrices. Hence, it can
be more efficient to group a number of SMs together in order
to reduce the number of steps to the solution at the expense of
larger admittance matrices.
A 5-s simulation was performed for a 31-level MMC with
groups of 1 (AM), 5 (AM5), 10, and 30 SMs. The results given
in Table VII show that it is more efficient to create a subnetwork for 5, 10, or 30 SMs rather than produce a subnetwork
for each SM. This is an important result since splitting a simulation model into a smaller number of subnetworks tends to be
less time consuming for the user, can improve simulation speed,
and reduce the risk of application instability.
The ac fault test scenario (Section V-A-3) was performed
using an AM30 model to assess any change in the model's accuracy. The arm current waveforms for a TDM, AM, and AM30
are compared in Fig. 15 and the normalized MAE values for
the AM and AM30 model with respect to the TDM are given in
Table VIII. The results show that there is very little change.
VI. ANALYSIS AND RECOMMENDATIONS
The three detailed EMT models compared in this paper represent the converter's IGBTs and diodes using a simple two-state
resistance and are therefore not suitable for studies which require a detailed representation of the power-electronics devices,
such as the assessment of switching losses. The type of model
compared in this paper is typically employed for control and
protection studies where the converter dynamics are important.
Although the three models compared in this paper represent
the power-electronics devices in the same way their implementation is different, this has an effect on the accuracy of their
results. A key difference between the TDM and DEM used in
this paper is that the DEM does not use interpolation and the
key difference between the TDM and AM is that the solution
of the AMs is dependent upon information from different subnetworks at the previous timestep. These are the two most significant reasons why there is a small difference between the results produced by each model, particularly under transient conditions. The results in Table VIII have shown that even when
two models are based on the same modeling technique, but
implemented slightly differently, the simulation results are not
identical. Using the TDM as the benchmark, the DEM was generally found to be more accurate than the AM, and the AM was
also found to produce numerical errors when the converter is
blocked and the arm current changes direction.
The different implementation methods for the three models
have a significant impact on their simulation speed. The results
in this paper have shown that the DEM is the fastest and the
TDM is the slowest. The simulation times for the TDM increase
significantly more than the DEM and the AM as the number of
converter levels increase and, hence, the DEM and AM modelling techniques have great value when modeling MMCs with a
relatively large number of levels. The results in this paper have
shown that a model of a 61-level MMC based on DEM and AM
techniques is 43 and 14 times faster than the TDM, respectively.
In the DEM, the SM components are not visible to the user
and, therefore, this model is not suitable for studies which require direct access to the SM components. The TDM and AM
do allow the user access to the SM components and can therefore be easily modified for the required study.
It is for these reasons that the DEM is considered to be the
most suitable model for all studies which do not require access to the SM components. The AM should be considered for
studies which require access to the SM components and where
simulation speed is an important factor; however, great care
should be taken if the study requires the converter to be blocked.
The user is also advised to create a subnetwork for a number
of SMs rather than for each SM since this may reduce implementation time, simulation time, and the possibility of application instability. The TDM is recommended for studies which
require access to the SM components and for the converter to
be blocked. The TDM is also recommended when simulation
speed is not an important factor.
VII. CONCLUSION
This paper has presented the first independent comparison
of two previously developed MMC modelling techniques (AM
and DEM). It is has also presented the first independent verification of the AM, and the first independent verification of
the DEM in PSCAD. An MMC-HVDC test system was developed and the AM model and DEM modelling techniques
were compared against the TDM modeling technique in terms
of accuracy and simulation speed. The accuracy of the AM and
DEM models was evaluated graphically and numerically for
BEDDARD et al.: COMPARISON OF DETAILED MODELLING TECHNIQUES
587
steady-state and transient studies. The unique findings contained
within this paper have shown that the AM and DEM modelling techniques offer a good level of accuracy but that the DEM
is generally more accurate than the AM. The AM and DEM
models have been shown to simulate significantly faster than
the TDM, and the DEM is more computationally efficient than
the AM. However, the AM model does provide access to SM
components (which is not possible with the DEM) and so may
be considered when this is an important factor.
The AM model was found to have limited performance for
certain conditions when the converter is blocked. This finding
highlights the importance of this comparative study since it has
highlighted previously unreported shortcomings of discussed
modeling techniques. It was also shown that by modifying the
original AM by producing a subnetwork for a number of SMs
rather than for a single SM, the simulation run time could be
improved.
These results have been used to propose a set of modelling
recommendations (Section VI) which summarize the findings
of this study and offer technical guidance on state of the art of
detailed MMC modelling.
APPENDIX
MMC MODEL DETAILS
A. Detailed Equivalent Model
A summary of the DEM is presented here; however, further
information can be found in [2].
1) Nested Fast and Simultaneous Solution: The NFSS approach is best explained with the aid of an example [2]. The
equivalent admittance matrix for a network which is split into
two subsystems is given by
(21)
where
admittance matrices for subsystem 1 and
subsystem 2 respectively;
Fig. 16. SM circuit (left) SM equivalent circuit (right).
of size
and
two matrices
of size
, instead of a single matrix of size
. This example partitioned the original network into
two subsystems; however, the network can be split into many
subsystems. In the DEM, each converter arm is modelled as its
own subsystem.
The size of the admittance matrices for each converter arm
is related to the number of SMs; hence, for MMCs with a high
number of levels, the size of the admittance matrices to be inverted are still relatively large. To further improve the simulation speed, the DEM reduces each converter arm to a Norton
equivalent circuit.
2) Norton Equivalent Circuit for the Converter Arm: This
modelling method is based on converting a multinode network
into an exact, but computationally simpler, equivalent electrical
network using Thevenin's theorem. The IGBTs and antiparallel
diodes employed in each SM form a bidirectional switch and
can therefore be represented as a resistor, with two values
and
. The resistor value is dependent upon the firing signal
to the IGBT and the arm current direction
. The converter
is considered to be blocked when the both IGBT's are switched
off and, hence, the values of R1 and R2 are determined by the
arm current direction. The SM capacitor can be represented as
an equivalent voltage source
, connected in series with a
resistor
, as shown in Fig. 16.
The
and
values are determined from the following
analysis:
(25)
admittance matrices for the interconnections;
Solving (25) for
method gives
unknown node voltage vectors;
using the trapezoidal integration
source current vectors.
The number of nodes in subsystem 1 and subsystem 2 are
and , respectively. The direct solution of (21) for the unknown vector voltages requires an admittance matrix of size
to be inverted.
Rearranging the second row of (21) for
gives (22). Substituting (22) into the first row of (21) produces (23) which can
be rearranged for
, as given by
(26)
where
(27)
(28)
The voltage at the terminals of the SM is given by (29)
(22)
(23)
(24)
, calculated from (24) is then substituted into (22) to calculate . Once all unknown voltages are calculated, all currents
can then be calculated. This approach requires the inversion of
(29)
where
(30)
(31)
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IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 2, APRIL 2015
means that the model is not suitable for studies which require
internal converter access. Also reconfiguring the component for
other SM topologies is not straightforward since it needs to be
recoded for that specific topology, which can be complex and
time consuming. Half-bridge and full-bridge MMC equivalent
arm components are currently available to PSCAD users.
ACKNOWLEDGMENT
The authors would like to thank J. C. Garcia Alonso of the
Manitoba HVDC Research Centre for providing the equivalent
half-bridge MMC arm component used in the DEM model and
for his useful discussions.
Fig. 17. String of SM Thevenin equivalent circuits (left). Converter arm
Thevenin equivalent circuit (right).
Fig. 18. PSCAD half-bridge MMC arm component.
The SMs in each converter arm are connected in series. The
Thevenin equivalent circuits for each SM can therefore be combined to a single Thevenin equivalent circuit for each converter
arm, as shown in Fig. 17. where
(32)
(33)
The Thevenin equivalent circuit for the converter arm is converted to a Norton equivalent circuit for use by the main EMT
solver.
The process outlined in this section has reduced a multinode
network for each converter arm and converted it into a two-node
Norton equivalent circuit in the main EMT solver. This significantly reduces the size of the admittance matrix for the EMT
solver which improves the simulation speed. Since the main
EMT solver only considers a two-node network for each converter arm, the individual identities of each SM are lost; however, the Thevenin equivalent solver considers each SM separately and, therefore, the SM capacitor voltages and currents are
recorded.
PSCAD has developed a DEM model based on the work by
Udana and Gole. The component mask is shown Fig. 18. The
development of the DEM has a clear advantage over the TDM
in terms of simulation speed; however, there are some limitations. The user it not able to access the SM components, which
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Antony Beddard (S’14) received the M.Eng. degree
in electrical and electronic engineering from the
University of Manchester, Manchester, U.K., in
2009, where he is currently pursuing the Ph.D.
degree in VSC-HVDC technology.
He was with Alstom Grid, Stafford, U.K. His research is in HVDC technology for the connection of
offshore windfarms.
BEDDARD et al.: COMPARISON OF DETAILED MODELLING TECHNIQUES
Mike Barnes (M’96–SM’07) received the B.Eng.
and Ph.D. degrees in power electronics from the
University of Warwick, Coventry, U.K.
In 1997, he was a Lecturer with the University
of Manchester Institute of Science and Technology
(UMIST, now merged with The University of Manchester), Manchester, U.K., where he is currently
a Professor. His research interests cover the field
of power-electronics-enabled power systems and
advanced drives.
589
Robin Preece (GS’10–M’13) received the B.Eng.
degree in electrical and electronic engineering and
the Ph.D. degree in power system dynamics from
the University of Manchester, Manchester, U.K., in
2009 and 2013, respectively.
Currently, he is a Research Associate at the same
institution, investigating risk and uncertainty with respect to the stability of future power systems.