Strategy to enhance the low-voltage ride-through in photovoltaic system during multi-mode transition

Strategy to enhance the low-voltage ride-through in photovoltaic system during multi-mode transition

Solar Energy 153 (2017) 744–754 Contents lists available at ScienceDirect Solar Energy journal homepage: www.elsevier.com/locate/solener Strategy t...

1MB Sizes 0 Downloads 25 Views

Solar Energy 153 (2017) 744–754

Contents lists available at ScienceDirect

Solar Energy journal homepage: www.elsevier.com/locate/solener

Strategy to enhance the low-voltage ride-through in photovoltaic system during multi-mode transition N. Jaalam a,b, N.A. Rahim b,c,⇑, A.H.A. Bakar b, B.M. Eid b a

Faculty of Electrical & Electronics Engineering, University of Malaysia Pahang, 26600 Pekan, Malaysia UM Power Energy Dedicated Advanced Centre (UMPEDAC), Wisma R & D, University of Malaya, 59990 Kuala Lumpur, Malaysia c Renewable Energy Research Group, King Abdulaziz University, Jeddah 21589, Saudi Arabia b

a r t i c l e

i n f o

Article history: Received 20 January 2017 Received in revised form 24 May 2017 Accepted 25 May 2017

Keywords: Grid-connected photovoltaic Low-voltage ride-through Reactive power Active power

a b s t r a c t With the increasing capacity of distributed generation (DG) connected to the power grid, the future generation of photovoltaic (PV) systems are expected to provide a full range of voltage regulation during grid faults in order to enhance the low-voltage ride-through (LVRT) capability of a PV system. In such a condition, the DG should remain connected to the grid for reactive power support, thereby improving voltage profile. This paper aims to propose a control strategy of active and reactive power for a single-stage threephase grid-connected PV system to enhance the LVRT. The dynamic behaviours of the system were investigated by considering various scenarios such as varying irradiance, local load disconnection, and short circuits, at different locations during the multi-DG operation. Results confirm that the grid-connected PV system is able to remain connected to the power grid during steady-state and transient-state conditions without violating the grid code requirements. The established dynamic behaviour analysis model of the proposed control for grid-connected PV systems can be used in planning an operational strategy for a practical system. Ó 2017 Published by Elsevier Ltd.

1. Introduction With the upsurge in awareness about the necessity to reduce the world’s dependence on fossil fuels, DG systems based on renewable energy sources (RES) such as wind, solar and hydro have gained popularity. However, the total electricity generation based on these RES is not reliable as reverse power flow may occur and it may possibly contribute to grid failure which can affect the operation and control of the power system (Babacan et al., 2017; Bevrani et al., 2010). The literature review shows that more than 80% of the cause of poor power quality in developed countries is due to voltage disturbances such as voltage sags and short interruptions (Honrubia-Escribano et al., 2014; Moreno-Munoz et al., 2010; Perpinan et al., 2013). A short-term voltage sag may occur as a result of lightning strikes, short circuits or even when large loads are connected (Dirksen, 2013; Montero-Hernandez and Enjeti, 2002). When such faults happened in the past, the IEEE1547 allowed wind turbines (WT) to disconnect from the grid and reconnect it after a certain period of time. However, this stan⇑ Corresponding author at: UM Power Energy Dedicated Advanced Centre (UMPEDAC), Level 4, Wisma R&D, University of Malaya, Jalan Pantai Baharu, 59990 Kuala Lumpur, Malaysia. E-mail address: [email protected] (N.A. Rahim). http://dx.doi.org/10.1016/j.solener.2017.05.073 0038-092X/Ó 2017 Published by Elsevier Ltd.

dard (1547) was designed many years ago where the capacity of DG based on RES installation was small (Schauder, 2012; Balathandayuthapani et al., 2012). Nowadays, this practice is no longer efficient as it can contribute to voltage flickers or system instability and could lead to power outages if too many generating plants are being disconnected at the same time (Dirksen, 2013; Yang et al., 2015). This situation will affect a large number of customers. Though voltage sag generated from RES cannot be eliminated due to its stochastic nature, it can be mitigated (Ipinnimo et al., 2013). As a result, the recent grid codes require keeping the WT connected to the power grid for a pre-specified voltage sag value and duration during a fault condition. Considering the voltage sag problems associated with RES, a socalled grid code known as LVRT has been established. The main objective of LVRT is to maintain the grid voltage stability and to avoid gigantic loss of power during the faults (Carrasco et al., 2013; Kirtley et al., 2013). Consequently, the generation based on RES should stay connected to the grid during such faults and at the same time provides grid support by injecting a reactive power in order to avoid grid collapse (Schwartfeger and Santos-Martin, 2014; Sousa et al., 2015). Fig. 1 shows the LVRT limiting curves defined by Italy, Germany, Japan, China, Spain, USA, and Denmark. Generally, if the voltage drop value is above the curve for a given specific time, the generating plant should remain connected to

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

Nomenclature Acronyms AC alternative current BIPV building integrated PV CIGRE International Council for Large Electric Systems DC direct current DG distributed generation LVRT low-voltage ride-through MPPT maximum power point tracking PCC point of common coupling PI proportional integral PR proportional resonant PV photovoltaic RES renewable energy sources WT wind-turbine Symbol description abc natural reference frame ab stationary reference frame dq synchronous rotating frame id active current i⁄d active current reference id,max maximum allowed of active current

idnew⁄ iq iq⁄ iqnew⁄ Irated P Pinv Pload PPCC Q Qinv Qload QPCC S VDC Vg Vgn Vinv VL VL⁄ Vload

r

745

active current during LVRT reactive current reactive current reference reactive current during LVRT rated value of the grid inverter current active power inverter’s active power load’s active power PCC’s active power reactive power inverter’s reactive power load’s reactive power PCC’s reactive power apparent power DC link voltage grid voltage normal grid voltage inverter’s voltage load’s voltage load’s voltage reference load’s voltage irradiance

Fig. 1. LVRT requirements defined by different countries (Yang et al., 2014; Ma et al., 2012; Perpinias et al., 2015; Tang et al., 2015).

the grid and an injection of reactive current is needed to support the grid voltage. Due to the maturity of wind power technology and high penetration of wind power generation, the grid codes for WT already existed in many countries (Marinopoulos et al., 2011). However, implementation of grid codes for PV system is still in its early stage and specific standards vary from one country to another (Carrasco et al., 2013). Yang et al. (2014a) proposed a new control strategy for a 500 kW two-stage three-phase grid-connected PV system. This system operated without maximum power point tracking (MPPT) mode when a fault occurred. In this case, the active power was generated based on the voltage sag magnitude while the inverter injected the appropriate reactive current for the voltage recovery. A feed forward compensation term was also proposed to smooth the DC-link voltage. Nanou and Papathanassiou (2014) used twostage power processing for a 100 kW PV system. In this controlling method, a proportional-resonant (PR) compensator was employed to produce inverter output current while the proportional-integral (PI) controller was used to regulate the DC link voltage (VDC). In Yang et al. (2014b), a 1 kW two-stage single-phase gridconnected system was developed to test four reactive power injection strategies – constant average active power control, constant active current control, constant peak current control, and ther-

mally optimized control strategy. A 500 kW PV inverter test bench was built in by Carrasco et al. (2013) with two back-to-back inverters. A full-load test was conducted in the study with different types of voltage sag to test the LVRT capability. Additionally, Miret et al. (2013) and Sosa et al. (2016) injected reactive current for both positive and negative sequences to realize the voltage support control. While both systems were tested for different types of voltage sags, Sosa et al. (2016) also looked into the low and high power generation scenarios. A flexible active power control which is based on a fast current controller and a reconfigurable current selector was proposed in by Rodriguez et al. (2007). Wu et al. (2014) examined the system for an unbalanced grid fault (single-phase to ground) at a distance of 7.7 km from the point of common coupling (PCC). Meanwhile, the RES has been integrated to the low voltage smart micro-grid with energy storage coupling in compliance to the Italian Standards (Falvo et al., 2015; Graditi et al., 2015). Though the effectiveness of the above-mentioned system was confirmed for restoring the voltage drops, the dynamic performance in variable conditions including varying irradiance, fault distance and in cascaded DG outage is still inadequate. This paper proposes an approach to control the active and reactive powers when disturbances occur. In this study, dynamic

746

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

analyses are carried out to evaluate the behaviour of a gridconnected system during LVRT of a 1 MW single-stage threephase grid-connected PV inverter. The grid-connected test system is examined by considering several fault cases in different locations with varying irradiance and load disconnection including a multiDG operation mode. The paper is organized as follows: Section 2 states the existing problems and the contribution of PV system with an emphasis on the grid code requirements as a benchmark, Section 3 describes the control approaches developed for gridconnected PV system to be implemented in the normal and abnormal conditions, Section 4 discusses the obtained results in different scenarios on the test system and finally, the conclusion is addressed in Section 5.

2014; Kirtley et al., 2013; Yang et al., 2014a, 2014c). The survey conducted by International Council on Large Electric Systems (CIGRÉ) has pointed out that still there are not enough studies regarding the changing nature of a grid-connected PV power system with higher penetration of asynchronous generation (Cigréj, 2013). The same statement is also reported in (Balathandayuthapani et al., 2012; Weise, 2015; Wu et al., 2014), where the authors have agreed that power system dynamic research on the impact of the grid structure is still insufficient. As the smart grid is nowadays standardized in many utilities and industries around the world, a developed control technique for security operational criterion is needed for a single-stage PV inverter, particularly for a high PV penetration during LVRT.

2. Problem description

3. The proposed control strategy for single-stage gridconnected PV system

With the increasing level of DG penetration around the world, the impact of its integration has drawn much concern especially on the voltage stability issue (Aly et al., 2014). The DG’s sizes, location, impedance, load disturbance, and inverter control have an impact on the system voltage. Additionally, the environmental conditions also affect the operation of DG, especially for the PV system. The intermittent nature of the solar irradiance inhibits the PV from extracting its maximum power, which in turn may lead to voltage instability (Woyte et al., 2007). It is well known that the major cause of voltage sag is a fault in the power grid (Wang et al., 2013). This disturbance can cause an over-voltage at the inverter’s direct current (DC) side and an over-current at the alternative current (AC) side (Wang et al., 2013). If the voltage and current exceed the limits, it could lead to an inverter tripping as a protective measure. Normally, the voltage must not be more than 1.10 p.u and less than 0.85 p.u for continuous operation (Hassaine et al., 2014). To maintain the voltage level at the acceptable limit, the DG sources should be capable of providing reactive power (Q) to support the grid and Q can be regulated by changing the amplitude of its output voltage (Albuquerque et al., 2010). If the voltage drop is above the curve in Fig. 1 for a specific time value, the maximum Q injection is required during the severe voltage drop which is less than 0.15 s. However, the Q capability is limited by the inverter’s active power (P) and apparent power (S) as shown in Fig. 2. Accordingly, P can be determined by the maximum power supplied by the PV system (Albuquerque et al., 2010). Even though the inverter is designed to deliver the maximum P, P is often reduced temporarily to allow maximum generation of Q during faulty conditions (Erlich et al., 2006). The proposed strategy for controlling the P and Q will be discussed in Section 3.2. It is clear from the literature review that several works have been done to tackle the challenging problem of grid support during faulty conditions. However, most of the works have not covered a single-stage PV inverter especially for a large scale PV system (Balathandayuthapani et al., 2012; Nanou and Papathanassiou,

Q P Inverter limit

Smax Pmax

-Q (capacitive)

-Qmax, cap

0

+Qmax, ind

+Q (inductive)

Fig. 2. PV inverter reactive power capability.

For a grid-connected PV system, power electronics technology plays an important role for an efficient interaction of PV-DG with the utility grid (Blaabjerg et al., 2004). As the PV system produces electricity in DC form which may be varying considerably, an inverter is required to convert it to an AC form that needs to be fed into the utility grid (Shireen et al., 2014). In addition, the inverter is also responsible for the system control, performance optimization and synchronization with the grid (Hassaine et al., 2014). The inverter can be categorized into a single-phase or three-phase topology. The single-phase inverter can be used in building integrated PV (BIPV) system while the three-phase system is used in large-scale power plants (Matic-cuka and Kezunovic, 2014). On the other hand, depending on the number of power processing stages, PV system can be connected to the grid either using single-stage or two-stage configuration (Eid et al., 2014). In the single-stage configuration, the PV system is connected directly to the grid by a DC-AC inverter. In the two-stage configuration, a DC-DC converter is employed to boost the PV panel voltage before DC-AC inverter (Balathandayuthapani et al., 2012). In this study, the single-stage power conversion has been chosen due to its simple topology and high conversion efficiency (Mastromauro et al., 2012; Eid et al., 2015). Fig. 3 shows a general structure of a single-stage three-phase grid-connected PV system with basic and grid supporting functions, which is used in this study. The following subsections explain the concept used to control a singlestage grid-connected PV system in the normal and abnormal conditions to enhance its capability for LVRT. 3.1. The control principle of normal operation, iq⁄ = 0 For the grid-connected DG system, the control structure mainly consists of two cascaded loops – internal current control loop and external voltage control loop, as illustrated in Fig. 4. The first loop is used to regulate the grid current and is responsible for the protection and power quality issues (Yang et al., 2014). The function of the second loop is to control the VDC level which is important for the active power balancing in the system (Tang et al., 2013). The output of this loop is used as an active current reference (id⁄) whereas the reactive current reference (iq⁄) is normally set to zero for a unity power factor. This indicates that the system only produces an active power. The proposed control strategy for three phase PV system can be modeled using different reference frames such as stationary (ab), synchronous rotating (dq), and natural (abc) reference frames. This study has implemented the synchronous reference frame, where the grid current and voltage waveform are transformed to a reference frame which rotates synchronously with the grid voltage (abc – dq transformation) (Pouresmaeil et al., 2010). This

747

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

DC C

Lf

AC

Transformer

VDC Inverter

PV

VDC control

iPV vPV

PCC

Rf

Grid synchronization

Grid

ig

Current control

Basic Function

vg

LVRT control Ancillary Function

Fig. 3. A general structure of a single-stage three-phase grid-connected PV system.

vd v d*

VDC Control

vdc*

id*

DC link controller

vdc

PI

iq

-ωL

DC

Lf

PWM

id

-ωL

AC vq*

iq* = 0

Transformer

id abc

PI

Current control

Rf

iq

vq

ia,b,c

dq

θ

vd

PLL

abc vq

Grid

dq

va,b,c

abc – dq transformation Grid synchronization

Fig. 4. Current loop and voltage loop in synchronous reference frame control.

transformation has done using Clarke and Park’s transformation as shown in Eqs. (1) and (2) where f can be either a three-phase current or voltage. The grid synchronization during PV integration is then obtained using a phase-locked loop (PLL) (Jaalam et al., 2016).





2 3 " # fa 1 1 2 1 2 2 6 7 p p ¼ 4 fb 5 3 3 0 fb  23 2 fc

fa

fd fq





 ¼

cos h0

sin h0 0

 sin h

0

cos h



fa

ð1Þ



fb

ð2Þ

Subsequently, the maximum P and Q flowing through the inverter can be calculated by:



3 ðv d i d Þ 2

3 Q ¼ ðv d iq Þ 2

Q by adjusting iq⁄. During abnormal conditions, iq⁄ must be controlled to impose Q to the system. This can be achieved by employing a PI-based LVRT controller as depicted in Fig. 5. The error difference of the measured load voltage (vL) and reference load voltage (vL⁄) is first calculated. Note that the vL⁄ is the standard voltage for distribution network for the public grid in Malaysia. The PI control is then used to produce the required iq⁄ (later will be referred as iqnew⁄) during mode transition with LVRT. As for an active power control to enhance the LVRT, a current limiter is used to minimize the flow of P when Q is injected to ensure the balancing of energy flowing through the system. The amount of Q can be maximized using this technique. The operation of the proposed control is shown in Fig. 6. According to the

ð3Þ

Kp VL*

ð4Þ

3.2. Control strategy during abnormal condition, iq⁄ – 0 In the proposed LVRT control strategy, the parameters measured from the power grid and PV system are utilized to control

+

e Ki

VL

1_ S

From load bus Fig. 5. PI-based LVRT controller.

+

iqnew*

748

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

VDC control

Vdc*

Vg DC link controller

idn

Vgn * i Current dnew

vd vd* PI

limiter

iq

Vdc

-ωL PWM

id VL*

LVRT scheme

VL

-ωL

vq*

iqnew*

PI

vq

Current control

Fig. 6. The proposed control strategy of active and reactive powers with current limiter.

controlling algorithm of LVRT model in Eq. (5), the new calculated value of id⁄ (idnew⁄) is set based on the magnitude of voltage sag, which can be referred to the LVRT curve (Germany) in Fig. 1. If the grid voltage (vg) is higher than 0.9 of normal grid voltage (vgn), the system will follow the initial condition of active current (idn). If vg is in between 0.9 vgn and 0.3vgn, the controlling algorithm should act to regulate the idnew⁄. If vg is less than 0.3vgn (normally for severe grid fault), no id should be delivered to the system to avoid more power losses.

2

idn

6 V idnew  ¼ 4 2  2 V gng 0

Subsequently, the maximum allowed of active current (id,max) to be delivered to the grid can be determined through Eq. (6) (Yang et al., 2014a) where Irated is the rated value of the grid inverter current.

Id;max ¼ Irated 

v g > 0:9v gn 7 caseb : 0:9v gn P v g P 0:3v gn 5 casec : v g 6 0:3v gn

ð6Þ

Finally, the new P and Q can be calculated by:

3

casea :

qffiffiffiffiffiffiffiffiffiffiffi I2dnew

ð5Þ



3 ðv d idnew Þ 2

ð7Þ



3 ðv q idnew Þ 2

ð8Þ

Start

Vg measurement

Vg

Is 0.9Vgn?

No

No

Vg

Yes

No

Is 0.3Vgn ≤ V g 0.9Vgn for more than 0.6s?

Inject P & Q accordingly

Yes

Is 0.3Vgn for more than 0.15s?

Yes

Disconnect from the grid Inject Q accordingly, stop injecting P

End Fig. 7. Algorithm of the proposed control strategy.

Disconnect from the grid

749

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

Fig. 6 shows the structure of a decoupled active and reactive current controller for abnormal conditions proposed in this study along with the current limiter. To improve the performance of the PI controller, a cross-coupling terms and voltage feedforward control are implemented in the system. The control strategy is adopted to obtain an independent control of P and Q during LVRT in which, the VDC is regulated in accordance with the required idn. This idn will then be used as one of the inputs to solve Eq. (5) for determining idnew⁄ during transition process. On the other loop, the vL is regulated to produce the iqnew⁄. Subsequently, both reference and measured currents will be compared, and the PI-based controller will be used to eliminate the error. To simplify the proposed concept, the overall control strategy is illustrated in Fig. 7. In this algorithm, the Germany curve in Fig. 1 is used as a benchmark to validate the performance of the proposed control strategy in fulfilling the grid code requirement where no grid disconnection should be presented during fault conditions. One of the vital problems that counter the DG’s integration is the fault location as it is the most frequent cause of voltage sags (Patne and Thakre, 2008). Therefore, the model of the proposed strategy is counted to investigate the power flow in all buses during fault occurrence. The following equation is used for the investigation.



V I  Zl

ð9Þ

where

Table 1 System parameters. Rated power, Prated Open circuit voltage, Voc Grid voltage (PV side), Vg Grid voltage (grid side) Grid frequency, fg Switching frequency, fsw Output filter, Lf Number of series-connected modules per string Number of parallel string

1 MW 930 V 415 Vrms 11 kV 50 Hz 10 kHz 0.05 mH 17 200

PV model: SunPower SPR-305.

VL (V)

In this study, simulations have been carried out using MATLAB/ Simulink through the modeling of a 1 MW grid-connected PV inverter shown in Fig. 3. This system was examined for LVRT by considering the control strategy as described in Section 3. The parameters of the system used in this study are listed in Table 1. In order to verify the effectiveness of the proposed control strategy for LVRT capability, dynamic behaviour analysis was performed considering changes in irradiances, fault disturbance at different locations, and when the load being reconnected to the system. During the initial condition (0–2 s), the irradiance was set to 1000 W/m2. Then, it dropped to 500 W/m2 starting from 2 s until 6 s. Within this duration, a three-phase load (1 MW) was removed at 4 s. Following this event, the irradiance increased again to 1000 W/m2 at 6 s until the end of the simulation time. Finally, a balanced three-phase fault occurred at 8.0 s and cleared at 8.1 s respectively. 4.1. Dynamic behaviour of active and reactive power control Fig. 8(a)–(d) depicts a clear picture of the system responses during the normal and abnormal conditions. At the beginning, the irradiance (r) was set at 1000 W/m2 with a load connected to the system. When the level of irradiance decreased to 500 W/m2 at 2 s, vL and iqnew⁄ dropped significantly, but Q increased in order to stabilize the vL to its initial value. At 4 s, when the load was disconnected, iqnew⁄ increased while Q decreased. When the irradiance increased to 1000 W/m2 again at 6 s, iqnew⁄ increased further and Q decreased to maintain the vL. According to Eq. (4), the less the iqnew⁄, the more the Q will be injected. This fact can be observed during a fault (8.0–8.1 s), where the vL experiences a significant drop. During this event, the system is capable of injecting Q to its maximum value. Therefore, the voltage sag can be minimized. The most important thing is that the VDC can also be stabilized to its nominal value around 930 V along the transitions period.

σ = 1000 W/m2 Load disconnected

Fault

σ = 1000 W/m2 Load disconnected

250 240 230 0

Iqnew* (A)

4. Verification and simulation studies

σ = 500 W/m2 Load disconnected

σ = 500 W/m2 Load connected

σ = 1000 W/m2 Load connected

V = rms voltage during the fault I = rms current during the fault Zl = absolute value of line impedance, ohms per length unit d = distance to the fault, length unit.

1

2

3

4

5

6

7

8

9

10

6

7

8

9

10

6

7

8

9

10

6

7

8

9

10

Time (s) (a)

0 -0.5 -1 0

1

2

3

4

5

DC Link (V)

Q (kVar)

Time (s) (b)

1000 500 0 0

1

2

3

4

5 Time (s) (c)

1000 900 0

1

2

3

4

5 Time (s) (d)

Fig. 8. (a)–(d) System transition during irradiance variation, load disconnection, and a fault.

750

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

σ = 1000 W/m2 Load connected

σ = 500 W/m2 Load connected

Fault σ = 1000 W/m2 σ = 1000 W/m2 Load disconnected Load disconnected

σ = 500 W/m2 Load disconnected

270 VL without LVRT VL with LVRT

260

Load voltage (V)

250 240 230

250

220 210 200 200

7.9

190 0

1

2

3

4

5 Time (s)

8

8.1

6

8.2 7

8

9

10

Fig. 9. Load voltage with and without LVRT capability.

σ = 1000 W/m2 Load connected

Reactive power (kVar)

2000

σ = 500 W/m2 Load connected

Fault σ = 1000 W/m2 σ = 1000 W/m2 Load disconnected Load disconnected

σ = 500 W/m2 Load disconnected Q_inv

Q without LVRT Q with LVRT

1500

Q_inv

2000 1000

1000 0

500

8

8.2

6

7

0 0

1

2

3

4

5 Time (s)

8

9

10

Fig. 10. Reactive power compensation with and without LVRT capability.

Figs. 9 and 10 show the LVRT capability of a single-stage threephase grid-connected PV system with and without using the proposed control strategy. From Fig. 9, it can be seen that without LVRT, vL drop a little bit at the beginning of the simulation (0– 2 s) as the power is being consumed by the load. The vL further dropped when the irradiance decreased to 500 W/m2 at 2–4 s. When a three-phase fault occurred, a significant impact can be seen on the voltage profile. In contrast, the LVRT capability can be improved through the implementation of the proposed control strategy. Here, the vL can be stabilized in accordance with its nominal value. It should be noted that the voltage drop due to the disturbances is minimized as the Q has been injected based on the voltage drop pattern for an effective compensation. It is also evident from the vL and Q profiles of Figs. 9 and 10 that a fast recovery can be achieved when the fault was cleared. Fig. 11 shows a relationship between P and Q curve for a disturbance according to Eq. (5). As mentioned in Section 3.2, the inverter must stop injecting P produced by the PV plant to the utility grid especially in a severe grid voltage fault (case c) to maximize the amount of Q. This condition can be seen in the figure where P dropped to zero and maximum Q was produced. The P is allowed

to be transported as usual for case a only where vg is bigger than 0.9 vgn. In case b, id⁄new is regulated based on the controlling algorithm. 4.2. Fault location analysis For a fault location analysis, the system was subjected to a three-phase fault to ground lasting for 0.1 s. Three cases have been considered: (1) fault at the PCC, (2) fault at distance of 15 km from the PCC, and (3) fault at distance of 35 km from the PCC. The results for P, Q, V, and VDC are demonstrated in Table 2. The values classifying the fault location analysis together with changes in irradiance and load disturbances are also tabulated. The measurements were taken at the inverter, load and PCC buses. From Table 2, it can be summarized that the fault location did not give a noticeable impact to P, Q, V and VDC from the beginning of simulation (0–2 s). However, when the irradiance dropped at 2 s, a significant impact can be seen for P and Q. The farther the distance from the PCC, the less the contributions to the voltage sag. Thus, less Q is needed as demonstrated in the table. This result is true for the PCC’s reactive power (QPCC) and inverter’s reactive power (Qinv) for all cases. However, load’s reactive power (Qload)

751

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

Case a

Case b

Case b

Case a

Case c

Case a

8

9

3000 P Q

P (kW) and Q (kVar)

2500

3000 2000

2000

1000 0

1500

7.9

8

8.1

8.2

1000 500 0 -500 0

1

2

3

4

5 Time (s)

6

7

10

Fig. 11. Active and reactive power curve under all cases.

Table 2 System’s response during the faults at PCC, 15 km from PCC and 35 km from PCC. Cases

Fault location

Ppcc (kW)

Pinv (kW)

Pload (kW)

Qpcc (kVar)

Qinv (kVar)

Qload (kVar)

Vpcc (V)

Vinv (V)

Vload (V)

VDC (V)

Case 1: r = 100 W/m2 Load connected 0–2 s

PCC 15 km 35 km

439 438 437

1039 1038 1038

595 596 596

12 0 8

115 104 98

99 99 99

5887 5884 5883

239 239 239

238 239 239

930 930 930

Case 2: r = 500 W/m2 Load connected 2–4 s

PCC 15 km 35 km

105 108 109

488 488 488

589 592 593

155 103 75

256 199 163

98 99 99

5860 5850 5845

238 239 239

238 238 238

930 930 930

Case 3: r = 500 W/m2 Load disconnected 4–6 s

PCC 15 km 35 km

0 12 14

488 488 488

495 497 498

188 120 85

190 117 74

0 0 0

5875 5863 5856

239 240 240

238 239 239

930 930 930

Case 4: r = 100 W/m2 Load disconnected 6–8 s

PCC 15 km 35 km

535 533 532

1038 1038 1038

500 500 501

60 21 0

63 31 17.3

0 0 0

5904 5897 5893

240 240 240

240 240 240

930 930 930

Case 5: r = 100 W/m2 During fault 8–8.1 s Transient (T) and Steady state (S)

PCC (T) 15 km (T) 35 km PCC (S) 15 km (S) 35 km

5650 5400 5360 5400 5200 5100

950 956 934 1000 1040 1040

404 440 450 440 463 475

1938 1340 1050 1650 1000 630

1968 1450 1200 1650 1050 700

0 0 0 0 0 0

5340 5290 5250 5480 5371 5320

210 217 220 225 232 235

210 217 220 225 231 235

879 873 865 915 921 923

Case 6: r = 100 W/m2 Load disconnected 8.1–10 s

PCC 15 km 35 km

534 532 523

1038 1038 1038

500 500 5001

65 23 0.5

69 33 18

0 0 0

5905 5897 5893

240 240 240

240 240 240

930 930 930

is zero as no Q injection is needed since the load has been disconnected starting from Case 3. Most important, it can be seen that the proposed system is effective in injecting Q as the V is stable for all cases. Even though the voltage dropped is more than 30% during the three-phase fault, the system is able to minimize the impact to ±5% only. The VDC is also stable along the simulation. Therefore, the system can continue to operate as the grid code requirement is not violated. Figs. 12–15 show the behaviour of the system in selected fault locations. It is seen from Fig. 12 that Q was injected from the beginning as the load was initially connected. At 2 s, when the irradiance started to decrease, Q started to increase more to compensate the consumed P by the load as shown in Fig. 13. As the load disconnected at 4 s, Q also dropped to maintain the vL in Fig. 14. Correspondingly, when the fault occurred at 8.0 s, Q at the fault location (at PCC) increased to its maximum value as the drop voltage was huge. Finally, when the fault was removed, Q reduced again to balance the voltage. The VDC can also be stabilized to its nominal value around 930 V as seen in Fig. 15.

The aforementioned results are valid for all fault locations. The results confirm that the farther the distance from the PCC, the less the contribution to the voltage sag. This means that a longer feeder has higher impedance which results in a higher voltage rise (Tonkoski et al., 2012). Thus, Less Q is needed to stabilize the voltage. 4.3. Multi-DG operation analysis The LVRT capability was further tested in a multi-DG system with 1 MW rated power, and each was connected at the PCC. Fig. 16 illustrates the configuration of this system. It can be seen that each of the DG has different feeder distance with PV1 is connected directly to the PCC while PV2 and PV3 are located 15 km and 35 km away respectively from the PCC. Similarly, the fault was simulated at 8.0 s for 0.1 s to evaluate the impact of the cascaded system on the grid. For simplicity, the irradiance was maintained at 1000 W/m2 along the simulation time, and the load was disconnected at 4 s onwards.

752

N. Jaalam et al. / Solar Energy 153 (2017) 744–754 Q_inv

2000

fault at PCC fault 15km from PCC fault 35km from PCC

Q inverter (kVar)

1500

Q_inv

2000 1000

1000

0 7.9

500

8

8.1

8.2

0 0

1

2

3

4

5 Time (s)

6

7

8

9

10

Fig. 12. The inverter’s reactive power for different fault distances.

Q_inv

1100 1000

P (kW)

900 800 700 600 fault at PCC fault 15km from PCC fault 35km from PCC

500 400 0

1

2

3

4

5 Time (s)

6

7

8

9

10

Fig. 13. The inverter’s active power for different fault distances.

250 245

fault at PCC fault 15km from PCC fault 35km from PCC

V load (V)

240 235 250 230

240

225

230 220

220 215 0

7.9 1

2

3

4

5 Time (s)

8

8.1 6

8.2 7

8

9

10

Fig. 14. Load’s voltage for different fault distances.

It is found that the feeder distance test for the multi-DG system gives a significant result compared to the single DG which has been presented in Section 4.2 and Fig. 12. Note that, without LVRT function, the cascaded system has a high voltage especially when the load has been disconnected at 4 s. Hence, this voltage is lowered by consuming Q as shown in Fig. 17. Again, when the fault is trig-

gered at 8 s, Q is compensated to influence the voltage rise. It can be seen that the shortest feeder distance compensates the highest reactive value to stabilize the load and the grid voltage. This results confirm the quick response of the proposed control strategy and establish the fact that the longer the feeder distance, the less the impact of the Q compensation.

753

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

fault at PCC fault 15km from PCC fault 35km from PCC

1050

VDC (V)

1000 950 900 850 800 0

1

2

3

4

5 Time (s)

6

7

8

9

10

Fig. 15. DC link voltage for different fault distances.

DC C

LC filter

AC

PV1 (1MW)

Inverter DC

C

LC filter

AC

PV2 (1 MW)

15km

Fault

Inverter DC

C

Grid

π

LC filter

AC

PV3 (1 MW)

PCC

π

35km

Inverter Fig. 16. Multi-DG operation mode under study.

Q_inv

Q inverter (kVar)

1500

PV1 PV2 PV3 Q_inv

1000 1500 1000 500 0 -500

500

8

8.1

8.2

0

-500 0

1

2

3

4

5 Time (s)

6

7

8

9

10

Fig. 17. Reactive power compensation for multi-DG operation mode.

5. Conclusion This paper presents a developed control strategy for improving the LVRT capability of three-phase grid-connected PV system. The dynamic behaviour of the system is investigated to verify the effectiveness of active and reactive power support during abnormal conditions. The presented results confirm the effectiveness of the proposed control strategy in compensating the grid with the desired reactive power during varying irradiation and

load disturbances at different fault locations. This also proves that the DG can handle system disturbances that occur in the distribution line without losing its voltage stability when the proposed controlling scheme is applied, thus the system can remain connected to the power grid. The test in multi-DG operation mode was also conducted and the result has confirmed that the nearest DG connected to the PCC consumed more reactive power to minimize the voltage rise due to the cascaded system.

754

N. Jaalam et al. / Solar Energy 153 (2017) 744–754

Acknowledgement This work was supported by Ministry of Higher Education, Malaysia (MOHE) and University of Malaysia Pahang. The authors also thank the technical and financial assistance of UM Power Energy Dedicated Advanced Centre (UMPEDAC) and the Higher Institution Centre of Excellence (HICoE) Program Research Grant, UMPEDAC – 2016 (MOHE HICoE – UMPEDAC). References Albuquerque, F.L., Moraes, A.J., Guimarães, G.C., Sanhueza, S.M.R., Vaz, A.R., 2010. Photovoltaic solar system connected to the electric power grid operating as active power generator and reactive power compensator. Sol. Energy 84 (7), 1310–1317. http://dx.doi.org/10.1016/j.solener.2010.04.011. Aly, M.M., Abdel-Akher, M., Ziadi, Z., Senjyu, T., 2014. Assessment of reactive power contribution of photovoltaic energy systems on voltage profile and stability of distribution systems. Int. J. Electr. Power Energy Syst. 61, 665–672. http://dx. doi.org/10.1016/j.ijepes.2014.02.040. Babacan, O., Torre, W., Kleissl, J., 2017. Siting and sizing of distributed energy storage to mitigate voltage impact by solar PV in distribution systems. Sol. Energy 146, 199–208. http://dx.doi.org/10.1016/j.solener.2017.02.047. Balathandayuthapani, S., Edrington, C.S., Henry, S.D., Cao, J., 2012. Analysis and control of a photovoltaic system: application to a high-penetration case study. IEEE Syst. J. 6 (2), 213–219. http://dx.doi.org/10.1109/JSYST.2011.2162889. Bevrani, H., Ghosh, A., Ledwich, G., 2010. Renewable energy sources and frequency regulation: survey and new perspectives. IET Renew. Power Gener. 4 (5), 438– 457. http://dx.doi.org/10.1049/iet-rpg.2009.0049. Blaabjerg, F., Chen, Z., Kjaer, S.B., 2004. Power electronics as efficient interface in dispersed power generation systems. IEEE Trans. Power Electron. 19 (5), 1184– 1194. Cigréj, G., 2013. Coping with limits for very high penetrations of renewable energy. Sustain. Energy, May, pp. 45–46 (C1/C2/C6.18). Carrasco, J.E.G., Tena, J.M., Ugena, D., Alonso-Martinez, J., Santos-Martin, D., Arnaltes, S., 2013. Testing low voltage ride through capabilities of solar inverters. Electr. Power Syst. Res. 96, 111–118. http://dx.doi.org/10.1016/j.epsr.2012.10.011. Dirksen, J., 2013. Low voltage ride-through. Dewi Mag. 43, 56–60. Eid, B.M., Rahim, N.A., Selvaraj, J., El Khateb, A.H., 2014. Control methods and objectives for electronically coupled distributed energy resources in microgrids: a review. IEEE Syst. J. 30 (3), 1–13. http://dx.doi.org/10.1109/JSYST.2013.2296075. Eid, B.M., Rahim, N.A., Selvaraj, J., Williams, B.W., 2015. Electronically coupled distributed generation modeling and control strategies for microgrid applications. Int. J. Appl. Math. Inf. Sci. 7, 1–11. Erlich, I., Winter, W., Dittrich, a., 2006. Advanced grid requirements for the integration of wind turbines into the German transmission system. IEEE Power Eng. Soc. Gen. Meet. 2006, 1–7. http://dx.doi.org/10.1109/PES.2006.1709340. Falvo, M.C., Martirano, L., Sbordone, D., Ippolito, M.G., Telaretti, E., Zizzo, G., Ellipsis Pelligra, B., 2015. A comparison of two innovative customer power devices for smart micro-grids. In: 2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 – Conference Proceedings, pp. 1504– 1509. http://dx.doi.org/10.1109/EEEIC.2015.7165394. Graditi, G., Ippolito, M.G., Telaretti, E., Zizzo, G., 2015. An innovative conversion device to the grid interface of combined RES-based generators and electric storage systems. IEEE Trans. Industr. Electron. 62 (4), 2540–2550. http://dx.doi. org/10.1109/TIE.2014.2336620. Hassaine, L., Olias, E., Quintero, J., Salas, V., 2014. Overview of power inverter topologies and control structures for grid connected photovoltaic systems. Renew. Sustain. Energy Rev. 30, 796–807. http://dx.doi.org/10.1016/j. rser.2013.11.005. Honrubia-Escribano, A., Gomez-Lazaro, E., Molina-Garcia, A., Martin-Martinez, S., 2014. Load influence on the response of AC-contactors under power quality disturbances. Int. J. Electr. Power Energy Syst. 63, 846–854. http://dx.doi.org/ 10.1016/j.ijepes.2014.06.056. Nanou, I., Papathanassiou, A., 2014. Modeling of a PV system with grid code compatibility. Electr. Power Syst. Res. 116, 301–310. http://dx.doi.org/10.1016/ j.epsr.2014.06.021. Ipinnimo, O., Chowdhury, S., Chowdhury, S.P., Mitra, J., 2013. A review of voltage dip mitigation techniques with distributed generation in electricity networks. Electr. Power Syst. Res. 103, 28–36. http://dx.doi.org/10.1016/j. epsr.2013.05.004. Jaalam, N., Rahim, N.A., Bakar, A.H.A., Tan, C., Haidar, A.M.A., 2016. A comprehensive review of synchronization methods for grid-connected converters of renewable energy source. Renew. Sustain. Energy Rev. 59, 1471–1481. http://dx.doi.org/ 10.1016/j.rser.2016.01.066. Kirtley, J.L., El Moursi, M.S., Xiao, W., 2013. Fault ride through capability for grid interfacing large scale PV power plants. IET Gener. Transm. Distrib. 7 (9), 1027– 1036. http://dx.doi.org/10.1049/iet-gtd.2013.0154. Ma, L., Liao, H., Li, J., Yang, X., Tschegodajew, K., 2012. Analysis of Chinese photovoltaic generation system low voltage ride through characters. In: IEEE 7th International Power Electronics and Motion Control Conference, pp. 1178– 1182. Marinopoulos, A., Papandrea, F., Reza, M., Norrga, S., Spertino, F., Napoli, R., 2011. Grid integration aspects of large solar PV installations: LVRT capability and

reactive power/voltage support requirements. IEEE Trondheim PowerTech 1–8. http://dx.doi.org/10.1109/PTC.2011.6019324. Mastromauro, R.A., Liserre, M., Aquila, A.D., 2012. Control issues in single-stage photovoltaic systems: MPPT, current and voltage control. IEEE Trans. Industr. Inf. 8 (2), 241–254. Matic-cuka, B., Kezunovic, M., 2014. Islanding detection for inverter-based distributed generation using support vector machine method. IEEE Trans. Smart Grid 5 (6), 2676–2686. Miret, J., Camacho, A., Castilla, M., De Vicuna, L.G., Matas, J., 2013. Control scheme with voltage support capability for distributed generation inverters under voltage sags. IEEE Trans. Power Electron. 28 (11), 5252–5262. http://dx.doi.org/ 10.1109/TPEL.2013.2246190. Montero-Hernandez, O.C., Enjeti, P., 2002. Ride-through for critical loads. IEEE Ind. Appl. Mag., 45–53 Moreno-Munoz, A., De-La-Rosa, J.J.G., Lopez-Rodriguez, M.A., Flores-Arias, J.M., Bellido-Outerino, F.J., Ruiz-De-Adana, M., 2010. Improvement of power quality using distributed generation. Int. J. Electr. Power Energy Syst. 32 (10), 1069– 1076. http://dx.doi.org/10.1016/j.ijepes.2010.06.002. Perpinan, O., Marcos, J., Lorenzo, E., 2013. Electrical power fluctuations in a network of DC/AC inverters in a large PV plant: relationship between correlation, distance and time scale. Sol. Energy 88, 227–241. http://dx.doi.org/10.1016/ j.solener.2012.12.004. Perpinias, I.I., Tatakis, E.C., Papanikolaou, N.P., 2015. Optimum design of low-voltage distributed photovoltaic systems oriented to enhanced fault ride through capability. IET Gener. Transm. Distrib. 9 (10), 903–910. http://dx.doi.org/ 10.1049/iet-gtd.2014.0515. Pouresmaeil, E., Montesinos-Miracle, D., Gomis-Bellmunt, O., Bergas-Jané, J., 2010. A multi-objective control strategy for grid connection of DG (distributed generation) resources. Energy 35 (12), 5022–5030. http://dx.doi.org/10.1016/j. energy.2010.08.019. Patne, R., Thakre, L., 2008. Factor affecting characteristic of voltage sag due to fault in the power system. Serbian J. Electr. Eng. 5 (1), 171–182. http://dx.doi.org/ 10.2298/SJEE0801171P. Rodriguez, P., Timbus, A.V., Teodorescu, R., Liserre, M., Blaabjerg, F., 2007. Flexible active power control of distributed power generation systems during grid faults. IEEE Trans. Industr. Electron. 54 (5), 2583–2592. http://dx.doi.org/ 10.1109/TIE.2007.899914. Schauder, C., 2012. Impact of FERC 661-A and IEEE 1547 on photovoltaic inverter design. In: Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, pp. 1–6. http://dx.doi.org/10.1109/TDC.2012.6281681. Schwartfeger, L., Santos-Martin, D., 2014. Review of distributed generation interconnection standards. IEEE Electr. Power Conf. 172, 13. Shireen, W., Nagarajan, A., Patel, S., Kotti, R., Goli, P., 2014. A reliable low cost power electronics interface for photovoltaic energy systems. Sol. Energy 108, 370–376. http://dx.doi.org/10.1016/j.solener.2014.07.018. Sosa, J.L., Castilla, M., Miret, J., Matas, J., Al-Turki, Y.A., 2016. Control strategy to maximize the power capability of PV three-phase inverters during voltage sags. IEEE Trans. Power Electron. 31 (4), 3314–3323. http://dx.doi.org/10.1109/ TPEL.2015.2451674. Sousa, T., Morais, H., Vale, Z., Castro, R., 2015. A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context. Energy 85, 236–250. http://dx.doi.org/10.1016/j.energy.2015.03.077. Tang, C.Y., Chen, Y.T., Chen, Y.M., 2015. PV power system with multi-mode operation and low-voltage ride-through capability. IEEE Trans. Industr. Electron. 62 (12), 7524–7533. http://dx.doi.org/10.1109/TIE.2015.2449777. Tang, X., Tsang, K.M., Chan, W.L., 2013. Power conditioning system for gridconnected photovoltaic system. Sol. Energy 96, 187–193. http://dx.doi.org/ 10.1016/j.solener.2013.07.021. Tonkoski, R., Turcotte, D., El-Fouly, T.H.M., 2012. Impact of high PV penetration on voltage profiles in residential neighborhoods. IEEE Trans. Sustain. Energy 3 (3), 518–527. http://dx.doi.org/10.1109/TSTE.2012.2191425. Wang, S., Yao, X., Zhao, J., 2013. A novel low voltage ride through strategy of twostage grid-connected photovoltaic inverter. In: 1st International Future Energy Electronics Conference (IFEEC), pp. 400–405. Weise, B., 2015. Impact of K-factor and active current reduction during fault-ridethrough of generating units connected via voltage-sourced converters on power system stability. IET Renew. Power Gener. 9 (1), 25–36. http://dx.doi.org/ 10.1049/iet-rpg.2014.0116. Woyte, A., Belmans, R., Nijs, J., 2007. Fluctuations in instantaneous clearness index: analysis and statistics. Sol. Energy 81 (2), 195–206. http://dx.doi.org/10.1016/ j.solener.2006.03.001. Wu, D., Lin, C., Perumalla, V., Jiang, J.N., 2014. Impact of grid structure on dynamics of interconnected generators. IEEE Trans. Power Syst. 29 (5), 2329–2337. http:// dx.doi.org/10.1109/TPWRS.2014.2302636. Yang, F., Yang, L., Ma, X., 2014a. An advanced control strategy of PV system for lowvoltage ride-through capability enhancement. Sol. Energy 109, 24–35. http://dx. doi.org/10.1016/j.solener.2014.08.018. Yang, Y., Blaabjerg, F., Wang, H., 2014b. Low-voltage ride-through of single-phase transformerless photovoltaic inverters. IEEE Trans. Ind. Appl. 50 (3), 1942– 1952. Yang, Y., Enjeti, P., Blaabjerg, F., Wang, H., 2015. Wide-scale adoption of photovoltaic energy: Grid code modifications are explored in the distribution grid. IEEE Ind. Appl. Mag. 21 (5), 21–31. Yang, Y., Wang, H., Blaabjerg, F., 2014c. Reactive power injection strategies for single-phase photovoltaic systems considering grid requirements. IEEE Trans. Ind. Appl. 50 (6), 371–378. http://dx.doi.org/10.1109/APEC.2014.6803335.