A Developed Voltage Control Strategy for Unbalanced Distribution System During Wind Speed Gusts Using SMES

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Peer-review under responsibility of the organizing committee of CPESE 2016 doi: 10.1016/j.egypro.2016.10.177

Energy Procedia 100 ( 2016 ) 271 – 279

ScienceDirect

3rd International Conference on Power and Energy Systems Engineering, CPESE 2016, 8-12

September 2016, Kitakyushu, Japan

A developed Voltage Control Strategy for Unbalanced Distribution

System during Wind Speed Gusts Using SMES

Mohamed M. Aly

a*

, Emad A.Mohamed

a,b*

, Hossam S. Salama

a

, Sayed M. Said

a

,

Mamdouh Abdel-Akher

a

, Yaser Qudaih

b

a

Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt b

Department of Electrical and Electronics Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka 804-8550, Japan

Abstract

The fast response, high efficiency and long lifetime of superconducting magnetic energy storage (SMES) compared to other energy storage systems make it a preferable selection for energy storage solution for wind power generation. SMES has attracted many researchers to study its potential applications in power systems. This paper discusses a scheme of fuzzy logic controlled SMES to minimize the voltage fluctuations of three-phase unbalanced radial distribution systems connected to wind energy conversion system (WECS) with large scale penetration level of 30% during wind speed gusts. In this paper, wind turbine used is of squirrel cage induction generator (SCIG) with shunt connected capacitor bank for power factor improvement. SMES unit consists of superconducting coil, DC-DC chopper, step down transformer, power conditioning system, and cryostat/vacuum vessel. The control technique is based on fuzzy logic controller (FLC). The studied system is 33-bus three-phase unbalanced radial distribution system. The SMES and WECS were connected to weakest buses in the system, namely Buses18 and 33. The control strategy is discussed in details and the proposed system is evaluated by simulation in MATLAB/SIMULINK package. The simulation results demonstrate the performance of the proposed fuzzy-logic-controlled SMES in mitigating the voltage fluctuations under wind speed gusts.

Peer-review under responsibility of the organizing committee of CPESE 2016.

Keywords: Superconducting Magnetic Energy Storage (SMES); fuzzy logic controller (FLC); wind energy conversion systems (WECS), voltage

fluctuations, power levelling; wind speed gust.

1. Introduction

With the direction of the world to search for renewable energy systems (RESs), wind energy is considered one of the most dispersed RESs. The penetration of the wind energy is rapidly increasing with the enrollment of the private sector in many countries. However, the random variation of wind speed can cause fluctuation in the voltage of power systems [1]. In recent years, voltage instability has limited power transfers and threatened power system

_{* Corresponding author. Tel.: +20-115-435-4575; fax: +20-974-661-406; Tel.: +81-90-3661-3667; fax: +81-93-884-3203.}

E-mail address: [email protected]; [email protected]

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reliability [2].

Voltages at the client service entrance are maintained by utilities within an acceptable range to guarantee sufficient operation and lifetime of client equipment. This may be attained by on-load tap changing transformers (OLTC) and reactive power support [3]. OLTCs and reactive power devices are not sufficient to ensure suitable voltage regulation because the natural variability of wind generation can occur on a short timescale that the present equipment can’t deal with [4].

An energy storage system such as batteries [5], flywheels [6], superconducting magnetic energy storage (SMES) [7], etc. is very important to solve the problems of voltage fluctuations. However, the response of flywheel and battery system is too slow to compensate power fluctuation in distribution systems with wind farm. Furthermore, the battery system and flywheel have lower efficiency and shorter lifetime compared to SMES [8]. SMES among different types of energy storage methods is preferred due to several responsible reasons. The main advantage of SMES is that the time delay during charging and discharging process is quite short [9]. Furthermore, it has higher efficiency and longer life time.

SMES unit consists of step down transformer, DC-DC chopper, power conditioning system, superconducting coil, cryogenic refrigerator, and cryostat/vacuum vessel to keep the coil in the superconducting state [10]. The real and reactive power can be absorbed or released from the SMES coil according to the power requirements of the system. Therefore, it can increase the ability of the applied control and enhance reliability and accessibility of the system [11]. The enforcement of SMES with wind energy has been expanded to regulate the voltage fluctuations problem. SMES can improve the voltage stability of an electrical power system during the variations of wind speed.

Although the doubly fed induction generator (DFIG) type of machine is the favorite type of generators for wind energy conversion systems (WECSs), the installed capacity of the WECSs is overwhelmingly based on the traditional fixed-speed induction generator [12]. Therefore, addressing the application of this type of generator into power systems is still important. The applications of SMES on electrical power systems connected to fixed-speed WECSs have been demonstrated in the literature. Reference [10] discussed the effect of SMES on mitigating the voltage sag and swell incidents of electrical distribution system. Reference [13] discussed the transient stability enhancement of multi-machine transmission system connected to WECS. Moreover, the effect of SMES on mitigating the voltage sag and swell incidents of grid system connected to DFIG was discussed in [7]. However, minimization of voltage fluctuations of unbalanced distribution systems with large scale wind penetration level during wind speed gusts has never been studied.

This paper presents a new application of SMES to mitigate the voltage fluctuations of three-phase unbalanced radial distribution 33-bus system connected to WECSs with high penetration level of 30%. The SMES and WECS were connected to Buses 18 and 33, as they showed the worst voltage profiles. A proposed control system for the SMES was applied based on FLC with two inputs and one output. The benefits of using fuzzy logic controller (FLC) compared with the conventional controllers are listed in [14]. The inputs are the wind speed and SMES current variations. Each input and the output (the duty cycle) has five sets of membership functions. The adopted technique was found to improve the control performance, where SMES can absorb/deliver power from/to the system. The control technique of SMES is based on voltage source converter (VSC), DC-DC chopper using insulated-gate bipolar transistor (IGBT) and pulse width modulation (PWM). The charging and discharging of SMES are determined by the duty cycle of the chopper, which is controlled by FLC. The modeling of WECS, SMES unit, and FLC were simulated by MATLAB/Simulink package. The results show the impact of SMES in mitigating the voltage fluctuations of the studied system under wind speed gusts.

2. System Modeling 2.1. WECS model

The mechanical output power from the turbine is given by Eq. (1) [15].

Pm = 0.5

U

ʌCp(Ȝ,ȕ)R 2

Ȟ3

(1) Where: ȡ is the air density, R is the rotor radius, ҃ is the wind speed, and Cp is the coefficient of performance of

the turbine.

For SCIG, Cp (Ȝ, ȕ) is given by Eqs. (2) and (3) [16].

Cp(Ȝ,ȕ) = C1(C2/Ȝi – C3ȕ – C4)e –C5/Ȝi +C6Ȝi (2) 1/ 1/ 0.08 0.035/ 1 3 E E O Oi

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Values of C1 to C6 are: 0.5176, 116, 0.4, 5, 21, and 0.0068, respectively.

2.2. SMES model

The energy stored in the coil is given by Eq. (3) and the power of the superconducting coil is calculated from Eq. (4) [17].

E = 0.5LI2 (3)

P = dE/dt = LIdI/dt = VI (4)

Where: E is the stored energy of the SMES coil, P is the rated power of the SMES coil, L is the inductance of the SMES coil, I is the dc current in the SMES coil, and V is the voltage across the SMES coil.

2.3. Control strategy of SMES

The charging and discharging of SMES are determined by controlling the chopper duty cycle based on the FLC, as shown in Fig. 1. The different states of SMES with the duty cycle (D) are shown in Table 1.

The control system of the SMES unit is based on two inputs applied to the FLC; the change of wind speed, dw (the difference between the reference wind speed and the actual wind speed) and the change of SMES current, dIsm

(the difference between reference SMES current and actual SMES current). Each input and the output was fuzzified into five sets of Gauss mf-type membership functions (MFs). The MFs for input and output variables are shown in Figs. 2 (a) – (c) where the duty cycle can be calculated from Table 2.

Table 1. Rules of duty cycle

Duty cycle (D) State of SMES

D = 0.5 Standby

0 D < 0.5 Discharge

0.5 < D 1 Charge

Table 2. Fuzzy logic SMES rules

SMES current deviation (dIsm)

Speed deviation (dݝw) BN N Z P PB BN NO NO NO FD FD N C NO NO FD FD Z FC C NO D FD P FC FC C D D BP FC FC C NO D

BN = Big negative, N = Negative, Z = Zero, P = Positive, PB = Big Positive, C = Charge, FC = Fast charge, D = Discharge, FD = fast discharge, NO =No action.

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PLL Vabc Vdc + -+ -VGͲref VdcͲref VG abc/dq ɽ PI-1 PI-3 Iabc + + -PI-2 PI-4 dq/abc PWM VSC AC System Vdc SMES COIL Vsm FLC _PWM Switchs Gate DC-DC chopper control DC-DC chopper W REF WActual IREF IAcual dW dI

Fig. 1. SMES model with control of DC-DC chopper

(a) (b)

(c)

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3. Results and Discussions

Fig. 3 shows the studied distribution system. The complete data of the loads and branches’ impedance are found in [18]. To make the system unbalanced, loads were changed on the phases such that phase A consumes 30% of the total load, phase B consumes 20% of the total load, phase C consumes 50% of the total load. The SMES and WECS were divided between Buses 18 and 33 [19]. The SCIG and SMES parameters are given in Table 3 and Table 4, respectively. The wind speed gust is shown in Fig. 4 [20]. SMES system is initially operated at 50% of its maximum rated energy.

Fig. 3. The 33-bus distribution System

Table 3. SCIG Parameters

Parameter Symbol Value

Nominal power MVA 0.6/0.9

Voltage Vrms [v] 480

Stator resistance Rs [pu] 0.01965

Stator reactance Xs [pu] 0.0397

Rotor resistance Rr [pu] 0.01909

Rotor reactance Xr [pu] 0.0397

Magnetizing reactance Xm [pu] 1.354

Inertia constant H 0.09526

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Table 4. SMES Unit Parameters Component Value Energy capacity 2.65 MJ Coil inductance 0.50 H Rated current 3.25 kA DC Link Capacitor 10 mF

Fig. 5 (a) - (c) shows the active power supplied to the distribution system at buses 18 and 33 as well as the real and reactive power generated by the grid without and with SMES. Fig. 5 (a) and (b) show the effect of the charging and discharging of the SMES in levelizing the real power supplied to the distribution system from the grid and wind farm. Moreover, the reactive power released by the SMES helps in decreasing the reactive power generated by the grid. The reactive power generated by the grid dropped from more than 3.0 Mvar to less than 1.0 Mvar when using SMES. This decreases the current from the grid and increases the power factor.

(a) (b)

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Fig. 5. Real and reactive power supplied to the 33-bus (a) real power supplied at buses 18 and 33, (b) real power supplied from the grid, (c) reactive power supplied from the grid

The power leveling strategy as well as the reactive power released from the SMES during wind speed gusts helps in controlling the voltages of the distribution system. The voltage profiles of Buses 18 and 33 are shown in Fig. 6 (a) - (d) without and with SMES. Voltage profiles of other buses are not illustrated, as they have better profiles than Buses 18 and 33. Fig. 6 shows that the voltage profiles are greatly improved when using SMES. For Bus 18, the voltage magnitude increases from 0.93, 0.95, 0.89 pu to 1.03, 1.03, 1.0 pu for phases a, b, and c, respectively. For Bus 33, the voltage magnitude increases from 0.93, 0.95, 0.89 pu to 1.02, 1.02, 0.98 pu for phases a, b, and c, respectively.

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(a) (b)

(c) (d)

Fig. 6. Voltage profile of (a) Bus 18 without SMES, (b) Bus 18 with SMES (c) Bus 33 without SMES, (d) Bus 33 with SMES

The performance of the SMES unit is shown in Fig. 7 (a) - (d). Figs. 7 (a) shows that the SMES discharges real power at low wind speeds and charges real power at high wind speeds. Figs. 7 (b) shows that the SMES releases reactive power to support buses’ voltage. Figs. 7 (c) shows that the SMES energy doesn’t exceed the rated values The constant value of the voltage across the DC link, as shown in Fig. 7 (d), validates the control process.

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(c) (d)

Fig. 7. Performance of the two SMES units: (a) active power, (b) reactive power, (c) energy, (d) dc-link voltage

4. Conclusion

This paper discussed the strategy of power leveling in mitigating the voltage fluctuations of a 33-bus unbalanced three-phase distribution system connected to fixed-speed type WECS at high penetration level of 30% during wind speed gusts. FLC is applied on the SMES charging and discharging of the SMES active and reactive powers. The FLC is controlled by two inputs: wind speed and SMES current variations.

The results show that connecting SMES to the distribution system results in mitigating the voltage fluctuations during the wind speed gusts. The voltage profiles of the worst two buses were increased from less than 0.95 pu to about 1.0 pu. The voltage magnitude of the loaded phase increases from 0.89 pu to 1.03 and 0.98 pu. Moreover, reactive power released from the SMES helps in decreasing the reactive power transfers from the grid by more than 65%, which improves the power factor of the system.

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