This study proposes a new solution for the parallel operation of microgrid inverters in terms of circuit topology and control structure. A combined threephase fourwire inverter composed of three singlephase fullbridge circuits is adopted. Moreover, the control structure is based on adaptive threeorder slidingmode control and wireless loadsharing control. The significant contributions are as follows. 1) Adaptive slidingmode control performance in inner voltage loop can effectively reject both voltage and load disturbances. 2) Virtual resistiveoutputimpedance loop is applied in intermediate loop to achieve excellent powersharing accuracy, and load power can be shared proportionally to the power rating of the inverter when loads are unbalanced or nonlinear. 3) Transient droop terms are added to the conventional power outer loop to improve dynamic response and disturbance rejection performance. Finally, theoretical analysis and test results are presented to validate the effectiveness of the proposed control scheme.
I. INTRODUCTION
Microgrid is a lowvoltage network with different microsources and distributed loads operating to supply electric power for a local area. Most microsources are interfaced through power electronic converters to provide loads with reliable and highquality power
[1]

[4]
. In such systems, every power electric converter should be able to control independently without communication links because of the long distance among microsources
[5]
,
[6]
. Concurrently, power electric converters should be able to share the variable distributed loads in proportion with the power ratings of converters. To realize the function of power sharing without intercommunication, droop methods that emulate the behavior of large power generators are usually adopted
[7]

[11]
. The basic prerequisite for applying droop methods is that the equivalent output impedance of the converter should be resistive or inductive. However, in lowvoltage microgrids, output impedance is usually resistiveinductive and measuring or estimating is difficult, which makes proportional power sharing impossible
[12]
,
[13]
.
Output impedance is determined through circuit topology, control structure, and line impedance. A possible solution to the impedance problem is adding an inductor in a series with a converter output. However, this inductor is heavy and bulky, and causes imbalance among the three phases. Hence, another method that puts a virtual output impedance loop into the control structure is usually adopted
[14]
,
[15]
. Given that line impedance is predominantly resistive in lowvoltage microgrids, virtual resistiveoutputimpedance loop is used in this study. Transient droop terms are also added into the conventional droop control method to improve the dynamic response and disturbance rejection performance.
Problems on imbalance and harmonics are also important in the parallel operation of microgrid inverters
[16]
,
[17]
. The output performance and robustness of microgrid inverters are mainly affected by the effectiveness of the control strategy
[18]

[25]
. In the past decade, various closedloop control techniques were reported to achieve the dynamic characteristic and disturbance rejection performance under different types of loads, such as proportionalintegral control
[18]
, proportionalresonant control
[19]
,
[20]
, Lyapunovfunctionbased control
[21]
, H∞ control
[22]
, and fuzzy control
[23]
. However, most of these works are only suitable for threephase balanced circuit or singlephase circuit, which could also not meet all load conditions, such as unbalanced loads and nonlinear loads. Recently, some works focused on the slidingmode control method. In
[24]
, a robust slidingmode controller is proposed to control the active and reactive powers of a doubly fed induction generator wind system without involving any synchronous coordinate transformation. However, the unbalanced condition is not considered in the study. In
[25]
, a combined fuzzy adaptive slidingmode voltage controller is used for threephase uninterruptible power supply (UPS) inverter. Moreover, in
[26]
, Mohamed et al. present a directvoltage control strategy for microgrid converters based on slidingmode dynamic controller. All these methods can realize robust operation in isolated or gridconnected modes, but output performance is quite poor because of chattering. Hence, this study presents a voltage regulation strategy based on adaptive threeorder slidingmode control. Meanwhile, to solve the unbalanced problem, a combined threephase fourwire inverter composed of three singlephase fullbridge circuits is adopted.
The remainder of this paper is organized as follows. Section II describes the system which involves the circuit topology and the basic principle of decentralized parallel operation. Section III presents the adaptive threeorder slidingmode voltage control with a virtual resistiveoutputimpedance loop and wireless load sharing control. Section IV shows the test results, which demonstrate the effectiveness and applicability of the proposed control strategies. Finally, Section V presents the conclusion.
II. SYSTEM DESCRIPTIONS
Fig. 1
shows a general microgrid system that consists of distributed generation (DG) units, distributed loads, and voltage source inverters (VSIs) that transfer the energy of DG units into an AC bus. VSIs generally operate in gridconnected mode, and power is transmitted from DG units into the grid. When a fault occurs or the power quality worsens in the utility, the microgrid system disconnects from the grid by cutting off switch S1 and entering intentional islanding mode. DG units and VSIs should be able to share variable distributed loads in proportion with the power ratings of the units and maintain AC bus voltage.
General microgrid system.
 A. Topology and Modeling
Distributed loads are usually unbalanced in actual microgrids, and sometimes singlephase loads are dominant. Hence, in terms of inverter design, the serious load imbalance problem should be considered primarily. The VSI shown in
Fig. 2
(a) is then adopted for the microgrid power converter in this study, which is composed of three singlephase fullbridge circuits (T1–T12), lowpass filters (
L_{f}
and
C_{f}
), and an isolated transformer (T).
R_{f}
is the perphase resistance of the
LC
filter, and
Z_{line}
is the impedance of the line.
u
and
i
are the output voltage and current of the modular inverter circuit respectively, while
v_{o}
and
i_{o}
are the output voltage and current of the lowpass filter respectively. Subscripts a, b, and c represent the three phases. Each phase in the topology can also be controlled independently.
Topology of the inverter and the equivalent dynamic model. (a) Topology of the threephase fourwire inverter. (b) Equivalent dynamic model of the single phase.
Before analyzing the VSI model, the following assumptions are made: 1) the isolated transformer T is ideal, and the turn ratio of the transformer is 1:1; 2) all switching devices are ideal, and the delay time can be disregarded. Therefore, the dynamic equation of every phase in the VSI can be represented as follows:
where
K_{PWM}
the equivalent parameter of the modular inverter circuit,
v_{con}
is the input control signal, and
K_{PWM} v_{con}
represents the output voltage of the modular inverter circuit. Eqs. (1) and (2) can be represented as
Through Laplace transformation, the dynamic model of the single phase shown in
Fig. 2
(b) can be obtained.
 B. Power Sharing Control
Fig. 3
shows the schematic diagram of a microgrid with two distributed generations.
U
∠0 is the AC bus voltage, and
E
_{1}
∠
ϕ_{1}
and
E
_{1}
∠
ϕ_{2}
are the output voltages of the two inverters.
ϕ_{i}
is the phase angle difference between the output and bus voltages.
r_{i}
emulates the sum of the output and line resistances, while
X_{i}
is the sum of the output and line inductances. The active power and reactive power of inverter
i
can be represented as
Equivalent circuit of a microgrid with two inverters.
where 
Z_{i}
 is the impedance amplitude of inverter
i
,
and
θ_{i}
is the impedance angle.
Assuming that the impedance of the inverter is resistive (
Z_{i}
=
R_{i}
), the active and reactive powers become
To realize the power sharing function, conventional droop characteristics are usually used in the parallel operation of microgrid inverters:
where
ω_{i}
^{*}
and
E_{i}
^{*}
are the nominal angular frequency and voltage of the inverter respectively.
m
and
n
are the droop coefficients.
 C. Output Impedance of the Inverter
Droop control and powersharing accuracy rely on the impedance angle and amplitude respectively. However, given the existence of line and output impedance differences between the two inverters, the accurate value of the equivalent output impedance is difficult to measure or calculate
[14]
. In this situation, a method that adds virtual impedance loop into control action is proposed. With a suitably designed virtual impedance, the equivalent output impedance of the inverter can effectively experience either inductive or resistive, and powersharing accuracy can be greatly improved. In
[15]
, the relationship between equivalent output impedance and power rating of the inverter is derived in detail.
III. CONTROL DESIGN
This section aims to propose a controller that can guarantee parallel operation of microgrid inverters with robust performance and accurate power sharing. The proposed control structure of a microgrid inverter is shown in
Fig. 4
. The structure consists of three main control loops: 1) inner voltage regulation loop, 2) virtual output impedance loop, and 3) outer P/Q sharing control loop. Given the particularity of the inverter topology adopted in this paper, the inner voltage regulation loop and virtual output impedance loop are controlled independently for each phase, whereas the outer P/Q sharing control loop is calculated for all the phases lumped together.
Proposed control structure of the inverter.
 A. Inner Voltage Regulation Loop
The main objective of the inner voltage regulation loop is to maximize the disturbance rejection performance and have an excellent voltage tracking performance. Based on Eq. (3), the state equation of the single phase can be represented as follows:
where
x
(
t
) =
v_{o}
,
u
(
t
) =
v_{con}
,
a_{p}
= −
R_{f}
/
L_{f}
,
b_{p}
= −1/
C_{f}L_{f}
,
c_{p}
=
K_{PWM}
/
C_{f}L_{f}
, and
n
(
t
) represents the sum of all uncertainties caused by parameter variation and dynamic and load disturbances.
n
(
t
) is assumed to be bounded (
n
(
t
)<
ρ
).
Define a voltage tracking error
e
=
v_{o}

v_{cmd}
and a threeorder dynamic sliding surface
s
(
t
) as
where
v_{o}
is the system output voltage,
v_{cmd}
is the reference voltage command, and
k_{1}
and
k_{2}
are nonzero positive constants.
As shown in
Fig. 5
, the proposed control scheme in every phase is composed of three parts: equivalent model controller, switching controller, and adaptive observation. The function of the equivalent model controller is to specify the desired performance based on the inverter model, and the output voltage of this controller is
u_{tr}
. The objective of switching controller is to suppress uncertainties and unpredictable perturbation to ensure the equivalent model controller performance, and the output voltage is
u_{sw}
. Adaptive observation is designed to alleviate the chattering phenomenon, which is inevitable in the slidingmode control method. By estimating the upper bound of the uncertainties, the observation can choose the control gain
adaptively. According to the dynamic model, the control law can be designed as follows:
Block diagram of the output voltage closed loop based on adaptive slidingmode control
where
λ
is a positive constant.
To prove the voltage control law, a Lyapunov function candidate is defined as follows:
where
The derivative of the Lyapunov candidate function is
According to Eqs. (12)–(17), the following can be obtained:
Based on the analysis above, the stable behavior of the adaptive threeorder slidingmode voltage control can be ensured, and the proposed control scheme has no strict requirement for the model parameters. The method of control parameter selection and the analysis of the inverter equivalent output impedance are then described in the following.
By comparing Eqs. (3) and (12), Eq. (19) can be obtained:
Through Laplace transformation, Eq. (19) can be represented as follows:
where
Z_{o}
(
s
) is the outputimpedance transfer function.
Fig. 6
shows the equivalent circuit of the inverter. Based on Eq. (20), the dynamics of the output voltage is affected by the output impedance of the inverter, and the desired dynamic response can be obtained by adjusting the system poles with the suitable selection of
k_{1}
and
k_{2}
.
Fig. 7
shows the root locus for different
k_{1}
and
k_{2}
values. Evidently, the poles gradually come close to an imaginary axis as
k_{2}
decreases, hastening the system but making it more oscillatory. In comparison, when
k_{1}
is increased, the poles move farther away from the real axis, resulting in a less damped system.
Equivalent circuit of the inverter with the inner voltage regulation loop.
Rootlocus diagrams. (a) k_{1}=9×10^{9} for 0≤ k_{2}≤2×10^{5}. (b) k_{2}=1.4×10^{5} for 5×10^{9}≤k_{1}≤1×10^{10}.
Table I
lists the detailed parameters of the 3φ fourwire inverter. The bode diagram of the output impedance can then be obtained, as shown in
Fig. 8
. The output impedance value clearly has comparable resistive and inductive terms at 50, 150, 250, 350 Hz, and so on. For example, at the power frequency (50 Hz), the output impedance is about −50 dB, and 80 deg, whereas if line impedance is considered, the output impedance is about −30 dB and 10 deg.
DETAILS OF THE 3Φ FOURWIRE INVERTER
DETAILS OF THE 3Φ FOURWIRE INVERTER
Bode diagram of the output impedance with and without the line impedance.
The phase and amplitude of output impedance is very sensitive to line impedance. Nevertheless, line impedances are difficult to measure and estimate in an actual system; line impedances are usually different among various inverters and even differ among the three phases of an inverter. Thus, powersharing accuracy among parallel inverters is not guaranteed.
 B. Virtual ResistiveOutputImpedance Loop
To meet the requirements of parallel operation for microgrid inverters, virtual output impedance loop is added into the control structure. By dropping the output voltage reference
v^{*}_{cmd}
proportionally to the output current, as shown in
Fig. 4
, the equivalent output impedance of the closedloop inverter can be changed and fixed. The input reference voltage of the inner loop can then be rewritten as
where
Z_{o}
^{*}
(
s
)=
R_{d}
+
Z_{o}
(
s
) is the new equivalent output impedance of the inverter, and
v
^{*}
_{cmd}
is the voltage reference at no load.
Fig. 9
shows the influence of
Rd
on output impedance. Increasing the value of
Rd
leads to increasingly resistive output impedance at the frequencies of 50, 150, 250, 350 Hz, and so on. Concurrently, the magnitudes of the output impedance at such frequencies tend to 20 lg
Rd
. Apparently, as
Rd
increases, the values of the original output and line impedances can be neglected. However, excessive
Rd
value would reduce the voltage reference considerably and cause the steadystate error of the system to increase. Accordingly, through proper design of the
Rd
value, the powersharing accuracy of the parallel operation for inverters can be ensured, regardless whether the loads are balanced, unbalanced, or nonlinear.
Bode diagram of the output impedance with Rd variation (from 0 to 1).
 C. Outer P/Q Sharing Control Loop
As shown in
Fig. 10
, the outer P/Q sharing control loop can be divided into three parts: power calculation, modified P/Q droop, and reference voltage generation. Given the existence of unbalanced loads, the method to calculate the active and reactive powers for each phase is adopted. The instantaneous active and reactive powers can be expressed as follows:
Block diagram of the powersharing controller.
where
v_{o}
and
i_{o}
are the measure values of the output voltage and current for each phase respectively, and
H
(
i_{o}
) demonstrates the Hilbert transform of
i_{o}
. Next,
p
and
q
should be processed by lowpass filters (LPFs). Subsequently, the total active and reactive powers are the sum of the three phases. In the figure, subscripts a, b, and c represent the three phases.
In microgrid dynamics, lowfrequency oscillation modes generated by powersharing controllers and power filters are dominant
[25]
. To enhance the performance of a conventional droop controller, transient droop terms can be added into Eq. (8). Transient droop functions increase the controllability of the powersharing controller by adding a second degree of freedom in control turning. The modified droop functions are given by
where
m_{d}
and
n_{d}
are transient droop coefficients. The proposed control method allows transient response to be modified by acting on the main control parameters while maintaining the static droop characteristics. In addition, the proposed method minimizes the transient circulating current among the modules and further improves the whole system dynamic performance. Coefficients
m
and
n
fix the steadystate control objectives, while
m_{d}
and
n_{d}
are selected to guarantee stability and excellent transient response.
To investigate the stability and transient response of the system, smallsignal analysis is performed
[27]
. Considering the effect of LPFs, the smallsignal dynamics of active and reactive powers [Eqs. (6) and (7)] can be expressed as
where
ω_{c}
/(
s
+
ω_{c}
) is the LPF,
ω_{c}
is the cutoff frequency, and
denote the perturbed values of
E_{i}
and
ϕ_{i}
respectively. By differentiating Eqs. (24) and (25), the following are obtained:
According to Eqs. (26)–(29), the following dynamics can be obtained:
The characteristic equation of the closeloop system can then be obtained as follows:
where
A
=
R_{i}
+
m_{d}ω_{c}U
cos
ϕ_{i}
B
=
ω_{c}
[2
R_{i}
+ (
n_{d}E_{i}
+
m
+
m_{d}ω_{c}
)
U
cos
ϕ_{i}
+
m_{d}n_{d}ω_{c}E_{i}U
^{2}
/
R_{i}
]
C
=
ω_{c}
[
R_{i}ω_{c}
+ (
nE_{i}
+
n_{d}ω_{c}E_{i}
+
mω_{c}
)
U
cos
ϕ_{i}
+ (
mn_{d}
+
m_{d}n
)
ω_{c}E_{i}U
^{2}
/
R_{i}
]
D
=
ω_{c}
^{2}
nUE_{i}
(cos
ϕ_{i}
+
mU
/
R_{i}
)
According to the characteristics in Eq. (32), system poles can be fixed. System stability and desired dynamical response can then be obtained by adjusting these poles with suitable selection of
m_{d}
and
n_{d}
. Using the inverter parameters listed in
Table I
, the rootlocus diagrams for different
m_{d}
and
n_{d}
values are illustrated in
Fig. 11
.
Fig. 11
(a) clearly reveals that by decreasing
n_{d}
, system poles will be close to an imaginary axis, making the system become oscillatory and even unstable.
Fig. 11
(b) indicates that by increasing
m_{d}
, firstorder dynamics will be increasingly dominant, whereas decreasing
m_{d}
makes the secondorder dynamics become dominant. Hence, transient droop coefficients can be obtained.
Rootlocus diagrams. (a) m_{d}=1×10^{5} for 0≤ n_{d}≤1×10^{5}. (b) n_{d}=1×10^{6} for 0≤ m_{d}≤2×10^{4}.
IV. RESULTS
This section evaluates the performance of the proposed controller and the parallel operation for the microgrid system depicted in
Fig. 1
through simulation and experiment. The test involves two DG units. Both the topologies adopt combined threephase inverter circuits, as shown in
Fig. 2
. The circuit and control parameters are presented in
Table 2
.
Fig. 12
(a) shows the experimental setup. Only singlephase fullbridge circuits are used in the inverters because of the particularity of the combined threephase fourwire topology. The design capacities are 5 and 2.5 kW. The composition of INV1 is shown in
Fig. 12
(b). Depending on the loads, the results of the three cases are discussed in the following sections:
Experimental setup.
PARAMETERS OF THE INVERTERS FOR PARALLEL OPERATION
PARAMETERS OF THE INVERTERS FOR PARALLEL OPERATION
 A. Case 1: Resistive Load
In this scenario, the simulation and experiment results of sudden load increase and reduction are considered. The initial load of every phase is set as 3 kW, and the load change value is 2 kW.
Figs. 13
and
14
show the simulation results of the parallel inverters. The commands of sudden load increase and reduction are set in
t
= 0.1 and 0.3 s respectively. In
Fig. 13
(a), symbols 1 and 2 represent the output currents of INV1 and INV2 respectively. Obviously, the inverters share the load current proportionately to its power ratings, and the control performance of the transient dynamics is very well that the currents can stabilize in one circle.
Fig. 13
(b) indicates that output voltage can remain stable when load changes, and the total harmonic distortion (THD) is less than 5%. However, given the existence of virtual resistiveoutputimpedance loop, very small variations (
t
= 0.1 and 0.3 s) occur on the output voltage and are almost negligible here.
Fig. 14
shows the instantaneous power for load and parallel inverters.
P
and
Q
represent the active and reactive powers. Evidently, load power can be shared in proportion with the power rating of the inverter.
Simulation results under resistive loads. (a) Aphase currents of the load, INV1 and INV2. (b) Load voltage.
Simulation results under resistive loads. (a) Active power (upper trace) and reactive power (lower traces) responses of the loads. (b) Power responses of INV1. (c) Power responses of INV2.v
The experiment results are shown in
Fig. 15
. The upper trace is load voltage, and the lower traces are output currents of the two inverters. The output current of INV1 is nearly double of INV2 regardless of whether the inverters operate in steady or transient state. Meanwhile, voltage stability is unaffected by the transient state.
Experiment results under resistive loads: load voltage (upper trace) and output currents (lower traces) of INV1 and INV2.
The simulation and experiment results show that the proposed control structure is effective for parallel inverters under resistive loading condition, and powersharing accuracy and dynamic response can be ensured.
 B. Case 2: ResistiveInductive Load
Resistiveinductive loading condition with a sudden change is considered in this scenario.
The simulation results are shown in
Figs. 16
and
17
. The initial loads of every phase are set as
P
= 3 kW,
Q
= 1 kVar, and the load change values are
P
= 1 kW,
Q
= 2 kVar. The variation commands of the loads are set in
t
= 0.1 and 0.3 s.
Fig. 16
shows the output voltage and current responses of the two inverters. The output currents of INV1 and INV2 are proportional to the power rating of both inverters, and resistiveinductive load cannot affect the powersharing accuracy and stability of the output voltage. Meanwhile, the current dynamics can stabilize within two circles.
Fig. 17
shows the performance of the instantaneous power. Compared with the resistive loading condition, the transient response is longer.
Simulation results under resistiveinductive loads. (a) Aphase currents of loads INV1 and INV2. (b) Load voltage.
Simulation results under resistiveinductive loads. (a) Active power (upper trace) and reactive power (lower traces) responses of the loads. (b) Power responses of INV1. (c) Power responses of INV2.
To test the robustness of the proposed control structure, pure inductive loads are added to the system in the experiment, as shown by the results in
Fig. 18
. The transient voltage disturbances are effectively rejected because of the robust slidingmode control performance. Furthermore, the power sharing accuracy between the two inverters is ensured.
Experiment results under resistiveinductive loads: load voltage (upper trace) and output currents (lower traces) of INV1 and INV2
 C. Case 3: Unbalanced and Nonlinear Loads
Unbalanced and nonlinear loading conditions are considered in this scenario.
To test the robustness of the proposed control strategies in rejecting unbalanced disturbances, unbalanced loads are added into the system in the time period 0.1 s <
t
< 0.3 s. The simulation performance of the load voltage and current under unbalanced loads are shown in
Figs. 19
(a) and
19
(b). The three phase current amplitudes and phases differ, but the load voltage remains balanced. The threephase voltages are balanced because of the special topology used in this study. The output current waveforms of INVs are shown in
Figs. 19
(c) and
19
(d). The current amplitudes of INV1 and INV2 are proportional to the power ratings of both inverters. The current phases of INV1 and INV2 are also the same; thus, powersharing accuracy under unbalanced loading condition is ensured.
Simulation results under unbalanced loads. (a) Load voltage. (b) Load current. (c) INV1 output current; and (d) INV2 output current.
To test the robustness of the proposed control strategies under nonlinear loading condition, the uncontrolled rectifier circuit is used, and load power is set to 10 kW. The simulation results are shown in
Fig. 20
.
Fig. 20
(a) shows the load voltage waveform, and the frequency spectra of this waveform are analyzed in
Fig. 20
(c). The output voltage, which yields a THD of 1.21%, is regulated to reject nonlinear load disturbances. The load and output currents of the INVs are shown in
Fig. 20
(b). The frequency spectra are correspondingly analyzed in
Figs. 20
(d)–
20
(f). The THDs of these currents (35%, 34.95%, and 35.19%) are nearly the same.
Simulation results under nonlinear loads. (a) Load voltage. (b) Aphase currents of the load, INV1 and INV2. (c) Load voltage spectra. (d) Load current spectra. (e) Output current spectra of INV1. (f) Output current spectra of INV2.
In the experiment, the load power of the singlephase uncontrolled rectifier circuit is set to 1 kW; the results are shown in
Fig. 21
. Compared with the simulation results, the load voltage and output currents have higher THDs. However, the powersharing accuracy is maintained. The inverters share not only the fundamental currents, but also the harmonic currents. Thus, powersharing accuracy under nonlinear loading condition is ensured.
Experiment results under nonlinear loads: load voltage (upper trace) and output currents (lower trace) of INV1 and INV2.
The aforementioned results show that the proposed adaptive slidingmode control and dynamic load sharing control can be used effectively and reliably under different loading conditions for the parallel operation of microgrid inverters.
V. CONCLUSION
A new solution for the parallel operation of microgrid inverters in terms of circuit topology and control structure is proposed in this study. The threephase fourwire inverter composed of three singlephase fullbridge circuits is adopted. The control structure consists of three nested loops: 1) inner voltage regulation loop, 2) virtual output impedance loop, and 3) outer P/Q sharing control loop. Adaptive slidingmode control is used in the inner voltage loop for the output voltage of the inverter to effectively reject load disturbances, regardless whether loads are balanced, unbalanced, or nonlinear. In a precise contrast with the conventional droop method and the actual lowvoltage microgrid, virtual resistiveoutputimpedance loop is used to enforce the equivalent output impedance of the inverters to be resistive and proportional. Finally, a new wireless powersharing control method that involves transient droop terms is adopted in the outer P/Q sharing loop. Consequently, excellent powersharing accuracy can be achieved for all kinds of loads: balanced, unbalanced, or nonlinear. Meanwhile, system stability and dynamic response can also be improved. Finally, theoretical analysis and test results verify the effectiveness and superiority of the proposed control structure.
Acknowledgements
This work was supported by the National Nature Science Foundation of China under Grant 51479018, and by the Fundamental Research Funds for the Central Universities under Grant 3132014322.
BIO
Qinjin Zhang was born in Jiangsu, China in 1986. He received his B.S. and M.S. degrees in Electrical Engineering from Dalian Maritime University, Dalian, China in 2009 and 2011 respectively. He is currently pursuing his Ph.D. in Marine Engineering from Dalian Maritime University, Dalian, China. His current research interests include distributed power generation technology, power electronics converters, and microgrids.
Yancheng Liu was born in Liaoning, China. He received his B.S. and M.S. degrees in Electrical Engineering from Harbin Industrial University, Harbin, China, and his Ph.D. degree in Marine Engineering from Dalian Maritime University, Dalian, China in 1985, 1988, and 2002, respectively. He is currently a professor in the Marine Engineering College at Dalian Maritime University, Dalian, China. His current research interests include AC motor control, power electronic converters, ship electrical propulsion technology, renewable energy systems, and microgrids.
Chuan Wang was born in Liaoning, China in 1985. He received his M.S., B.S., and Ph.D. degrees from the Marine Engineering College, Dalian Maritime University, Dalian, China in 2007, 2009, and 2012, respectively. He is currently a lecturer in the Marine Engineering College in Dalian Maritime University, Dalian, China. His current research interests include power systems, intelligence artificial algorithms, particle swarm optimization, and system identification.
Ning Wang was born in Shandong, China in 1983. He received his B.Eng. degree in Marine Engineering and Ph.D. degree in Control Theory and Engineering from Dalian Maritime University, Dalian, China in 2004 and 2009 respectively. From September 2008 to September 2009, he was financially supported by the China Scholarship Council to work as a jointtraining Ph.D. student at the Nanyang Technological University, Singapore. He is currently an Associate Professor in the Marine Engineering College in Dalian Maritime University, Dalian, China. His research interests include AC motor control, robust control theory, artificial neural networks, fuzzy systems, machine learning, and ship intelligent control.
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