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An accurate reactive power control study in virtual flux droop control

  • Aimeng Wang EMAIL logo and Jia Zhang
Published/Copyright: December 29, 2017

Abstract

This paper investigates the problem of reactive power sharing based on virtual flux droop method. Firstly, flux droop control method is derived, where complicated multiple feedback loops and parameter regulation are avoided. Then, the reasons for inaccurate reactive power sharing are theoretically analyzed. Further, a novel reactive power control scheme is proposed which consists of three parts: compensation control, voltage recovery control and flux droop control. Finally, the proposed reactive power control strategy is verified in a simplified microgrid model with two parallel DGs. The simulation results show that the proposed control scheme can achieve accurate reactive power sharing and zero deviation of voltage. Meanwhile, it has some advantages of simple control and excellent dynamic and static performance.

PACS: 88.05.Ec

1 Introduction

Due to environmental, social and geographical constraints, traditional power supply is almost saturated. In recent years, microgrid technology has developed rapidly, which provides a new choice for traditional power grid [1]. There are two main modes of operation in microgrid: grid connected mode or islanded mode. When faults occur, microgrid will automatically separate from the large power grid, which ensures the flexibility and reliability of power supply [2].

Reactive power sharing among DGs is an important research field of microgrid. Virtual impedance is introduced to decouple active and reactive powers in low voltage microgrid. However, the drop of voltage will be increased with the adoption of virtual impedance [3,4]. Ref. [5] uses the high reactive power droop gain, which reduces the error of reactive power sharing at the expense of system stability. Ref. [6] improves the accuracy of reactive power allocation by injecting small real power disturbances. But in this method active and reactive powers affect each other, and the control performance is sensitive to the load change. In [7], an adaptive voltage droop control strategy is proposed with the consideration of voltage drop across transmission line and reactive power sharing. Nevertheless, the strategy needs to know the parameters of lines and system stability can be affected by some small errors.

All the aforementioned control schemes are based on voltage-frequency droop method, which requires multiple feedback loops and PI regulations. Ref. [8] proposes a novel virtual flux droop control method, where flux and angle can be controlled by a direct flux controller without complex multiple feedback loops and PI regulations. The control strategy is very simple and has excellent static and dynamic performance.

This paper proposes a novel reactive power control strategy based on virtual flux droop. The paper is organized as follows: In section 2, flux droop control method is introduced briefly for further study. In section 3, the factors influencing reactive power sharing are analyzed. On this basis, a new reactive power droop controller is designed with the consideration of accurate reactive power sharing and voltage recovery. In section 4, a simulation is conducted in a microgrid model to verify the effectiveness of the proposed control strategy.

2 Virtual flux droop control

The equivalent circuit of an inverter in microgrid is shown in Figure 1. In Figure 1, L and R are the line parameters; V, E and I denote inverter side voltage, load side voltage and the line current respectively; ϕV and ϕE represent the phase angle of V and E; P and Q are the average real and reactive powers.

Figure 1 Equivalent circuit of an inverter in microgrid
Figure 1

Equivalent circuit of an inverter in microgrid

The following relations can be obtained for highly inductive transmission line

V=LdIdt+E(1)
S=P+jQ=IE(2)

ΨV and ΨE are the inverter side flux and load side flux which are obtained by the time integration of V and E. They satisfy

ψV=tVdt(3)
ψE=tEdt(4)

Combining (1)(3)(4), the following formula can be obtained

I=ψVψEL(5)

By substituting (4)(5) into (2), powers supplied to the load can be obtained

P=wψVψELsinδ(6)
Q=wψEL(ψVcosδψE)(7)

Considering the value of δ is typically small, active and reactive powers can be controlled by δ and |ΨV|, respectively. Thus the virtual flux droop formulas can be obtained

δ=δnm(PPn)(8)
ψV=ψVnn(QQn)(9)

where δn and |ΨV|n are the nominal flux angle difference and amplitude of inverter flux; Pn and Qn are the rated active and reactive powers; m and n are the droop coefficients of the P - δ and Q — |ΨV|.

Figure 2 is the overall control structure of flux droop method, which consists of two parts: flux droop controller and direct flux controller. As shown in Figure 2, |ΨV|refand δref from flux droop controller are compared with their actual values to get deviation signals. Then, deviation signals combined with the current position of inverter flux are used to select the proper voltage vectors according to a switching table during each period [9]. The control system is simple and has excellent control performance.

Figure 2 The overall control block diagram of flux droop control
Figure 2

The overall control block diagram of flux droop control

3 The novel reactive power control strategy based on virtual flux droop method

3.1 Factors affecting reactive power distribution

Figure 3 shows the equivalent circuit of power sharing between two parallel DGs. In Figure 3, |ΨVi| and ϕfVi are the inverter flux amplitude and angle (i = 1, 2); PL and QL are the load demand powers.

Figure 3 The power sharing circuit of two parallel DGs
Figure 3

The power sharing circuit of two parallel DGs

When the voltage drop of transmission line is considered (Note that the line resistance can be neglected in this paper), the relationship between V and E can be expressed as

VE=QXVQXE(10)

According to (3)(4), the relation between the amplitude of flux and voltage is

V=wψV,E=wψE(11)

Substituting (11) into (10), the difference between |ΨVi|and |ΨE| is

ψViψE=nLiQi(12)

where nLi = Li/(w |ΨE|), and it can be seen from the expression of nLi that nLiLi(i = 1,2).

According to (9), the flux amplitude difference can be obtained with the assumption of n1Q1 = n2Q2

ψV1ψV2=n2Q2n1Q1(13)

According to (12), the flux amplitude difference can be

ψV1ψV2=nL1Q1nL2Q2(14)

Combining (13)(14), the reactive power distribution formula can be obtained

Q1Q2=n2+nL2n1+nL1(15)

It can be seen from (15) that the accuracy of reactive power sharing is affected by droop gains as well as line impedance. Due to the disperse geographical locations of DGs, the line impedance usually does not satisfy the inverse proportional relationship to DGs’ rated capacities, so the reactive power sharing error is usually unavoidable.

3.2 The novel reactive power droop controller

Figure 4 is the principle diagram of the proposed power control strategy, which includes active power control and the novel reactive power control. The novel reactive power controller consists of three parts: reactive power compensation control, flux droop control and voltage recovery control, which ensures accurate power sharing and voltage recovery simultaneously. Because the main purpose of this paper is the allocation of reactive power, active power control is not discussed here.

Figure 4 The novel control structure of  the proposed  power control strategy
Figure 4

The novel control structure of the proposed power control strategy

Reactive power compensation control is mainly to implement accurate reactive power sharing without affecting system stability. In reactive power compensation control, the reactive power deviation from rated power of i-th DG is given by

ΔQi=QiQin(16)

The sum of reactive power deviation is

ΔQtot=i=1NΔQi(17)

where N represents the number of DG units participating in reactive power distribution.

Correction value of reference flux amplitude can be obtained

ΔψViref1=kc(ciΔQtotΔQi)(18)

where compensation coefficient kc is all the same for DGi, and its value is closely related to the stability of system, so it should be properly selected. ci is the partition coefficient, which is determined by droop gains

ci=1/nij=1N(1/nj)(19)

The main purpose of voltage recovery control is to maintain the value of output voltage at rated level. Its expression is

ΔψViref2=kv(EnEi)dt(20)

where voltage recovery coefficient kv is also the same for every DG, |En| and |Ei| denotes the amplitude of nominal and actual output voltage.

By combining these three control modules, the expression of the novel reactive power controller can be obtained

ψViref=ψVnni(QinQi)+kc(ciΔQtotΔQi)dt+kv(EnEi)dt(21)

After obtaining the values of |ΨVi|ref and δiref, they are sent to direct flux controller and controlled directly by two hysteresis comparators, which is as shown in Figure 2. The proposed control scheme can implement accurate reactive power sharing as well as voltage recovery. Meanwhile, it has some advantages of simple control and excellent control performance.

4 Simulation and analysis

To verify the effectiveness of the novel reactive power control strategy, a simplified microgrid model with two parallel DGs is built by Matlab/Simulink, as shown in Figure 5 [10]. The parameters of two parallel DGs are all the same except for the line inductance, which are listed in Table 1.

Figure 5 Simplified microgrid model with two parallel DGs
Figure 5

Simplified microgrid model with two parallel DGs

Table 1

Simulation parameters

ParameterSymbolValue
DC voltageVdc1,Vdc210 KV
Line inductanceL18 mH
Line inductanceL210 mH
Line resistanceR1,R20.05 Ω
Filter capacitorC1,C2150 μF
Tie-line inductanceLt6 mH
Tie-line resistanceRt0.4 Ω
Load inductanceL11,L2240 mH
Load resistance 1R11,R2116 Ω
Load resistance 1R12,R2215 Ω
Nominal frequencyfn60 Hz
Nominal flux amplitude|ΨV|n7.797 Wb
Nominal voltageE1,E22950 V
Nominal reactive powerQ1n, Q2n0.2 MVar
Gain of Q-|ΨV| droopn1,n21e-6 Wb/Var
Compensation gainkc6e-4
Voltage recovery gainkv0.4

Figures 6(a) and 6(b) show the reactive power sharing before and after adopting the novel reactive power controller. In the example studied in this paper, reactive power sharing among two parallel DGs should be identical. However, there is reactive power allocation error in traditional flux droop control due to the mismatch of line inductance. In the proposed control strategy, compensation control can help eliminate reactive power sharing error and achieve accurate power sharing.

Figure 6 Reactive power sharing under two control strategies. (a) adopting traditional flux droop method. (b) adopting the proposed control  strategy
Figure 6

Reactive power sharing under two control strategies. (a) adopting traditional flux droop method. (b) adopting the proposed control strategy

In the novel reactive power control strategy, voltage recovery control can make the voltage deviation caused by droop control to be zero. Figure 7 shows the voltage amplitudes of two parallel inverters. It can be seen from Figure 7 that the output voltages of two parallel inverters are stabilized at the rated value.

Figure 7 The voltage amplitudes of two parallel inverters after adopting voltage recovery control
Figure 7

The voltage amplitudes of two parallel inverters after adopting voltage recovery control

In order to further verify the effectiveness of the novel reactive power controller, the output frequency and voltage are analyzed. Figure 8(a) is the output frequency, whose value is fixed around the rated value due to the adoption of angle droop instead of direct frequency droop control. From Figure 8(b), it can be seen that the output voltage is very stable and sinusoidal. Figure 8(c) is the Fourier analysis of the output voltage. It shows that the output voltage has good steady performance with only 0.47% of total harmonic distortion.

Figure 8 The voltage amplitudes of two parallel inverters after adopting voltage recovery control
Figure 8

The voltage amplitudes of two parallel inverters after adopting voltage recovery control

5 Conclusion

To solve the problem of inaccurate reactive power sharing in flux droop control, a novel reactive power control scheme is proposed in this paper. The following conclusions can be drawn by analyzing simulation results:

  1. In the novel reactive power controller, compensation control can effectively eliminate reactive power sharing error caused by the line inductance mismatch. Meanwhile, the voltage recovery control can maintain the output voltage at the rated value.

  2. The novel control strategy based on flux droop method is very simple which replaces complicated multiple feedback loops with direct flux control. What’s more, the proposed control scheme has better characteristics of voltage and frequency, where zero deviations of frequency and voltage can be obtained and voltage has excellent static performance as well.

Acknowledgement

The Open Subject of State Key Laboratory of Alternative Electrical Power System with Renewable Energy Sources (LAPS16023); Beijing Natural Science Foundation (3172037).

References

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Received: 2017-11-9
Accepted: 2017-11-12
Published Online: 2017-12-29

© 2017 Aimeng Wang and Jia Zhang

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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  227. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  228. Current superimposition variable flux reluctance motor with 8 salient poles
  229. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  230. Modelling axial vibration in windings of power transformers
  231. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  232. Field analysis & eddy current losses calculation in five-phase tubular actuator
  233. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  234. Hybrid excited claw pole generator with skewed and non-skewed permanent magnets
  235. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  236. Electromagnetic phenomena analysis in brushless DC motor with speed control using PWM method
  237. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  238. Field-circuit analysis and measurements of a single-phase self-excited induction generator
  239. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  240. A comparative analysis between classical and modified approach of description of the electrical machine windings by means of T0 method
  241. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  242. Field-based optimal-design of an electric motor: a new sensitivity formulation
  243. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  244. Application of the parametric proper generalized decomposition to the frequency-dependent calculation of the impedance of an AC line with rectangular conductors
  245. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  246. Virtual reality as a new trend in mechanical and electrical engineering education
  247. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  248. Holonomicity analysis of electromechanical systems
  249. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  250. An accurate reactive power control study in virtual flux droop control
  251. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  252. Localized probability of improvement for kriging based multi-objective optimization
  253. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  254. Research of influence of open-winding faults on properties of brushless permanent magnets motor
  255. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  256. Optimal design of the rotor geometry of line-start permanent magnet synchronous motor using the bat algorithm
  257. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  258. Model of depositing layer on cylindrical surface produced by induction-assisted laser cladding process
  259. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  260. Detection of inter-turn faults in transformer winding using the capacitor discharge method
  261. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  262. A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle
  263. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  264. Lamination effects on a 3D model of the magnetic core of power transformers
  265. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  266. Detection of vertical disparity in three-dimensional visualizations
  267. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  268. Calculations of magnetic field in dynamo sheets taking into account their texture
  269. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  270. 3-dimensional computer model of electrospinning multicapillary unit used for electrostatic field analysis
  271. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  272. Optimization of wearable microwave antenna with simplified electromagnetic model of the human body
  273. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  274. Induction heating process of ferromagnetic filled carbon nanotubes based on 3-D model
  275. Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2017
  276. Speed control of an induction motor by 6-switched 3-level inverter
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