A remote islanding detection and control strategy for photovoltaic-based distributed generation systems

Energy Conversion and Management 96 (2015) 228–241

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Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman

A remote islanding detection and control strategy for photovoltaic-based distributed generation systems Gökay Bayrak ⇑ Nevsehir Haci Bektas Veli University, Faculty of Engineering and Architecture, Department of Electrical and Electronics, 50300 Nevsehir, Turkey

a r t i c l e

i n f o

Article history: Received 19 December 2014 Accepted 1 March 2015

Keywords: Distributed generation Remote islanding detection Grid-tied PV system FPGA

a b s t r a c t This study presents a new remote islanding detection method and control system for photovoltaic (PV) based Distributed Generation (DG) systems. The proposed method monitors and controls the grid, local load and the output of the PV inverter in real time with the communication of circuit breakers. The proposed remote control system detects the changes in the currents of the circuit breakers, frequency, and the voltages by checking the defined threshold values at all electrical branches of the PV system. The proposed islanding detection algorithm was implemented by a low-cost FPGA board. The control system was also designed by considering a Very Large Scale Integration (VLSI) structure. The proposed method was verified by a developed prototype PV system constituted in the laboratory. The proposed control system was checked in a resonance condition with an active power match, and the verified results indicated that the developed system was also independent of the load and the inverter. Islanding detection time is approximately 1.65 ms even in a worst-case operational scenario, and this is a significantly shorter response time according to the existing standards. The proposed method presents a realistic solution to islanding, is easy to implement, and is suitable for real system applications. The method also provides a reliable islanding detection and presents a low-cost solution to the subject. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction PV technology has developed rapidly over recent years such that solar energy has become the most important source of renewables [1]. Grid-tied PV systems have been coming into prominence in Distributed Generation (DG) systems in parallel to this development. There are some restrictions in connecting PV systems to utility grids such as the reliability of the grid, providing high power quality and safe interaction with the PV system. Islanding is maybe the most important issue in this restriction for PV systems, providing a reliable connection and continual operation with the grid. Islanding operation is defined in a DG that a situation while a grid-tied PV system continues feeding the load, although disconnection of the electrical grid from the load [2]. Fig. 1 indicates a general schematic diagram of the grid-tied PV systems. Voltage and frequency of the system change from reference values in an islanding condition, so the grid disconnects from the grid-tied PV system without causing any damages to the system. Because of this, islanding detection methods have an important role in detecting the islanding in grid-tied PV systems.

⇑ Tel.: +90 3842281000; fax: +90 3842281123. E-mail address: [email protected] http://dx.doi.org/10.1016/j.enconman.2015.03.004 0196-8904/Ó 2015 Elsevier Ltd. All rights reserved.

The abnormal grid operating conditions negatively affect PV systems [3]. Islanding is the most significant security problem in a grid-tied PV system. Islanding operation can cause damage to both the PV system and the grid, and the grid voltage and the grid frequency are not stable in an islanding situation [4]. These conditions change from the grid reference values such that the circuit breaker (CB) connected between the grid and the point of common coupling (PCC) clears the fault during islanding mode. Meanwhile, DG still supplies power to the local load if the CB cannot open the circuit [5]. Voltage shutdown, equipment failure, and short-circuit conditions cause an unpredictable interruption of the grid, and these abnormal conditions cause islanding operation in a PV system [6]. Fig. 2 shows an islanding condition in a PV-based DG system [7]. There are two general types of islanding operations, intentional islanding and unintentional islanding [8]. Intentional islanding creates a power island when a disturbance occurs. An energy management plan is essential in an intentional islanding which is established to supply the local load consistently by DG [9]. Intentional islanding is a planned operation organized by the grid operators such that it is not harmful to the power system [10]. However, unintentional islanding can damage the grid due to loss of the synchronization of the electrical grid by causing a significant change in power system stability [11]. This situation causes the

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Fig. 1. A general schematic diagram of the grid-tied PV systems.

Pinv+jQinv

TR

Inverter

CB

Electrical Grid

Pload+jQload

DC/DC Converter

P+j Q

PCC

Electrical Load Fig. 2. Islanding in a PV-based DG system.

voltage and frequency to be out of desired grid reference ranges which can cause damage to the electrical devices and equipment of the system in the island DG section [12]. Because people working on the grid-tied PV system cannot realize that DG continues to supply power to the island part of the system, this situation presents a danger. The definition of this problem in a grid-tied PV system is an important criterion; islanding must be detected as soon as possible as indicated in IEEE standards [13]. This situation always should be considered carefully by authorized DG workers and companies. Consequently, a DG containing a PV system should be disconnected from the local load by using a circuit breaker which is triggered by a generated control signal because of these restrictions [14]. There have been many developments in islanding detection methods and algorithms described in the literature [15].

Islanding is an important problem to solve in PV based DG systems because it could cause serious problems with damaging equipment in PV system and the danger of death for working people. There have been some standards to define the rules and restrictions for grid-tied PV systems in islanding mode of operation. Mainly, IEEE-1547, IEEE 929, IEC-62116 and Japan standards are necessary for islanding. IEEE 929-2000 also defines frequency threshold values, voltage threshold values and required opening time for circuit breaker (CB) in PV based micro-grid systems. Table 1 shows these definitions and threshold values. Islanding is detected according to the nominal voltage, and frequency values compared with specified values in IEEE 929-2000. Table 1 also indicates the opening time of circuit breaker in defining the conditions for the islanding mode of operation.

2. Current islanding detection methods

2.1. Passive islanding detection methods

There are two main methods, referred to as local and remote detection methods [16,17]. Remote methods are related to measuring system parameters at a DG. In this study, a new remote method between DG and the grid is used.

Passive methods have a wide usage in PV based DG systems because of their smooth implementation and practical solution to the subject, and these techniques are the primary detection methods for detecting islanding. In addition, passive systems do not

Table 1 IEEE 929–2000 threshold values for grid connection. No

Frequency

Voltage

CB opening time

1 2 3 4 5 6 7 8

fnom fnom fnom fnom fnom (fnom  0.7) 6 f 6 (fnom + 0.5) Hz f < (fnom  0.7) Hz f > (fnom + 0.5) Hz

0.5 Vnom 0.5 Vnom < V < 0.88 Vnom 0.88 Vnom 6 V 6 1.10 Vnom 1.10 Vnom < V < 1.37 Vnom 1.37 Vnom 6 V Vnom Vnom Vnom

6 cycles 2 s/120 cycles Normal operation 2 s/120 cycles 2 cycles Normal operation 6 cycles 6 cycles

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produce any change in power quality. Passive methods have some drawbacks like having a large non-detection zone (NDZ) and setting threshold values with difficulty. These methods are unsuccessful for islanding detection, mainly the power balance of the load and the PV system. Active methods use passive methods in the background of the operation, so this situation has a negative impact on the power quality of the system. Power quality changes significantly in active methods, mainly connecting more inverters to the same DG. 2.2. Active islanding detection methods Active methods use a disturbing signal for detecting islanding mode of operation [18]. The disturbance signal changes in very short limitations when the grid connected; but when the grid disconnects from PV system, the interference signal has a significant difference according to the standard running condition. Fig. 3 also shows the overall structure of active methods in islanding mode of operation. 2.3. Remote islanding detection methods Remote methods have the best performance, according to the passive and active methods because of these methods all circuit breakers monitored by the control system. Installing sensors and telecommunication devices to the system makes these methods having high system and operation cost [19,20]. The power quality does not change, and the system is stable in remote methods. In addition, these techniques are used for the system cost is not necessary, according to power quality of the system [21]. The overall structure of remote methods also is shown in Fig. 4. 2.4. A short discussion of previous works The new islanding detection methods have been proposed in the last few years by the scientists, and most of them have been

researched an efficient and general detection method for the PVbased DG systems. Distributed grid integration of the PV systems is also an essential subject related to the islanding detection. A real-time dynamic model was proposed to determine the optimal size, location of a DG system into [22], and bidirectional power flow control was also researched into [23]. The main purpose of the studies is to manage the DG in real-time by providing the protection of the DG. Energy management is a significant issue to achieve a successful islanding detection, and controlling the active, and reactive power of the DG is another approach to detecting islanding [3,24]. A real-time Labview-based islanding detection system was also proposed in the last few years, and the remote control of the PV-based DG system was proposed in these studies [26,27]. A local energy management of a hybrid PV system was also considered into [28], and it is obvious that the researchers have been focused on real-time remote control techniques for the protection of DG systems in recent years. As a consequence of this approach, a newest study which is a smart device for islanding detection in distribution system operation [29] was proposed by Di Fazioa et al. There have been also some different approaches based on computational intelligence techniques on this subject recently [32]. Islanding protection using wavelet analysis and neuro-fuzzy system in inverter based distributed generation was researched into [16], and an adaptive ANN-controlled was proposed into [25] to reduce the NDZ consisting in passive islanding detection methods. Variable impedance insertion [30] and droop control [31] methods also offer different solutions to the subject. There have been a few FPGA-based islanding detection studies in recent years [32], but these studies present only particular, not general solutions to the problem. From the literature review, almost none of detection methods have a complete solution to the problem. Passive methods have a large NDZ and in matching the powers of inverter, load, and grid, they could fail to detect islanding. Active techniques have almost no NDZ, but they have a power quality problem in the system.

Iinv

Igrid=0

Idisturbance

TR

PCC

DC/DC Converter

CB

Electrical Grid

Iinv+Idistrurbance

Inverter

Electrical Load Fig. 3. The general structure of active methods.

TR DC/DC Converter

PCC

Inverter

CB T

R

Electrical Load Fig. 4. The overall structure of remote methods.

Electrical Grid

231

G. Bayrak / Energy Conversion and Management 96 (2015) 228–241 Table 2 A comparison of current islanding detection methods. Features

Local methods

Remote methods

Passive

Active

Hybrid

PLL

SCADA

Operation principle

Measuring the PCC parameters

Adding a disturbing signal to the grid

The combination of active and passive methods

Grid impedance change in PCC

NDZ Response time Detection failure

Large Short

Small Shorter than Passive Methods Yes only in highquality factor

Small Longer than Active Methods

No Fast

Using receiver and transmitter sensors between DG and grid No Faster

Smaller than Active and Passive Methods

No, except a few specific conditions

Yes

Yes, but smaller than Active Methods

No, except a few specific conditions No

Minimum cost No

Average cost Yes

High cost Yes

Very high cost No

Extremely high cost No

No

Decreases the power quality of the system

Decreases the power quality of the system, but smaller effect, according to Active Methods

No

No

Effect on dist. grid System cost Multiple inverter connect Effect on power quality

Yes, when matching powers of inverter, load, and grid No

No

experimental studies about this subject because of the mentioned limitations. Also, there are not any practical, and generalized existing experimental methods can be widely used in the real system applications. Reducing the NDZ, achieving a stable power quality and reducing the system cost in a PV-based micro-grid are the main objectives of islanding detection methods. While there have been many islanding detection methods described in the literature, there is only a real time application system in Japan [21]. Table 2 shows a comparison of current islanding detection methods. 3. The proposed remote islanding detection method Fig. 5. Non detection zone (NDZ) for passive methods.

Hybrid methods are still only hypothetical. Remote methods are possibly the best solution for islanding, but they have extremely high system and operating costs. Most of the proposed methods are still at the idealistic level only, and there have been a few

The passive islanding detection methods have some drawbacks like having a large non-detection zone (NDZ) and setting threshold values for difficulty and these methods are unsuccessful for islanding detection, especially the power balance of the load and the PV system [13]. Fig. 5 shows the NDZ, and it is very small in active

Proposed Islanding Detection&Control Software

FPGA Control Unit CBs Control Signals

EMC-1

EMC-2

Circuit Breakers PV Array (1 kWp)

DC/DC Converter

Inverter

CB-inv

Electrical Grid

CB-grid CB-load

EMC-3

Electrical Load Fig. 6. The proposed FPGA-based remote islanding detection system.

Current Sensor Voltage Sensor

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methods according to passive methods. There is a disturbing signal which is used in active methods and also over/under voltage and frequency passive methods are used with active methods, so this condition changes the power quality of the system. Power quality significantly changes in active methods, especially connecting more inverters to the same DG [14]. Remote islanding detection methods have the best performance, according to the passive and active methods. The proposed algorithm is independent of local load and inverter because it uses many parameters to detect islanding instead of measuring only the PCC voltage. Thus, the proposed method is not a passive method having NDZ changing by local load, and it is a communication based (coordination of the circuit breakers) method with no NDZ. In this study, the proposed method has a new remote method by using communication and control of the circuit breakers. The power quality does not change (because these methods are independent of local load and, they do not fail in a resonance condition), NDZ is zero, and the system is stable in communication based methods. There is no NDZ problem with this method because it checks all of the system parameters in real time, and it proposes a communication based method by using communication and control of the circuit breakers. The goal of the study also chooses a remote detection method to prevent the NDZ and, local load problems existing in passive and active detection methods. The proposed algorithm that is shown in Fig. 7 checks the currents of the circuit breakers which are placed on three sides of the PV system. If one of these currents goes to zero or they are under/ over defined threshold values, the circuit breakers have been tripped by using a communication based control system. This criterion is the main approach to detecting islanding in the proposed method. Thus, the proposed system does not measure only at the PCC voltage, and it is not the main control criteria for the proposed system. The proposed algorithm also controls the frequency, active power, and reactive power in addition to the currents, so it is reliable to detect islanding. Many methods focus on investigating the point of common coupling (PCC) and are thus limited to, use the load and have an NDZ problem. In this study, a new FPGA-based remote islanding detection method is introduced for PV-based DG systems. A real-time controller developed by the FPGA development unit manages the PV-based DG system for islanding detection. In the proposed method, grid, inverter, and load are monitored differently from other methods and loss of mains is checked by controlling the voltages, currents and frequency of the whole system. If one of these variables goes to zero or is outside of the selected threshold values, digital signals created by the FPGA board control the circuit breakers. Thanks to this structure, breakers clear the fault within only in a few cycles and islanding is independent of the load. Fig. 6 indicates the proposed FPGA-based remote islanding detection system. The proposed islanding detection algorithm detects the differences in threshold values of grid voltage and grid frequency. Fig. 7 indicates this proposed detection algorithm. A low-cost Altera DE0-nano board manages the algorithm. In this structure, voltages and frequency values of the grid, load and inverter output are measured. The proposed method, continuously checks the threshold values in real time. If detected values are over/under selected threshold values, control system counts the sample to check the islanding condition. And then a trigger signal is generated by the FPGA board which opens circuit breakers connected to the grid at the load and inverter output sides.

proposed PV system connected to the grid and its islanding detection block diagrams. The PV system generates the electrical power and interacts with the grid. If grid voltage or frequency is out of the limitations, circuit breakers are tripped, and the PV system disconnected from the grid. The proposed method has been tested for when the grid voltage is 260 V (rms) that provides the ‘300 V < Un < 253 V’ condition. When the grid voltage increases up to 253 V, the control system waits for five cycles to check the islanding condition, and then a trip signal triggers the circuit breakers. The developed simulation system also has been tested for different load conditions. Fig. 9 shows the resistive load (200 W) condition and also shows an inductive load condition (200 W and 400 VAR).

4. Developed FPGA and VLSI-based detection and control method The proposed islanding detection method was implemented by using an FPGA board. The proposed algorithm was designed by considering Very Large Scale Integration (VLSI) structure. The

Start

Measure V and f at load, grid and PV sides of the system

Control Difference Values Under/Over Threshold Values?

No

Yes

Count samples for checking the fault?

No

Yes

Trigger Circuit Breakers for Islanding

Disconnect PV system from grid and load

3.1. The simulink model of the proposed method A Simulink model of both the grid-tied PV system and the islanding detection system is implemented before constituting the experimental test bench. Fig. 8 shows the overall structure of

End Fig. 7. The proposed islanding detection algorithm.

G. Bayrak / Energy Conversion and Management 96 (2015) 228–241

233

Fig. 8. A simulation model of the proposed islanding detection method.

Fig. 9. (a) The resistive load condition (P = 200 W), (b) the inductive load condition (P = 200 W and QL = 400 VAR).

islanding detection algorithm runs with a low-cost Altera DE0Nano board. This frequency is also the maximum operating frequency for the proposed algorithm. Fig. 10 also shows the general schematic of the proposed control system in detail. FPGA board controls the inverter, load and the grid sides of the microgrid system. Electronic Measurement Cards (EMCs) have obtained the parameters just like voltage, current, and frequency. 0–10 V analog control signals are defined according to these parameters for managing the system by giving them to the analog inputs of the FPGA board. The current, voltage and frequency are obtained from microgrid with EMCs by using current and voltage sensors. The measured signals are converted to 0–10 V analog signals and are transmitted to the analog input channels of the FPGA

board. These signals are evaluated in FPGA board thanks to developed software with Quartus. All the parameters can be determined about the microgrid thanks to this structure. Fig. 11 shows the developed Electronic Measurement Card (EMC). Fig. 12 also indicates the implemented voltage measurement circuit which is shown in Fig. 11. 4.1. Developed real-time control and islanding detection software It is started to be researching FPGA based software for real-time monitoring of the developed microgrid. The developed software is improved for monitoring each side of the DG system (PV array, inverter, load, and grid) with Quartus. The voltage, current,

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frequency, active power, reactive power, apparent power, the phase angle and the peak values are determined in the developed software, and the DG system is monitored in real time. The developed software evaluates the analog inputs transmitted from electrical measurement circuits and according to these parameters, monitors the electrical parameters of the PV-based DG system. Fig. 13 shows the general structure of the developed software. Active power generated by the microgrid system, requested active power and transferred power to the grid can be monitored in real time in developed software. The line voltages, currents, the phase angle of the load, and the system frequency are also monitored by the software. Active and reactive power changes of the microgrid, load, and the grid can also be monitored together in real time with developed software. Developed software monitors all parameters of the DG system and detects islanding according to the defined threshold values in Table 3. In the study, an uncomplicated, suitable VLSI-based structure for voltage drifting detection is proposed. The system involves operating at very high speed. Fig. 14 shows the VLSI-based control system. Fig. 15 displays the modeling and monitoring schematic for the FPGA-based PV system. The MUX block operates as the circuit breaker due to logical ‘‘0’’ and logical ‘‘1’’. When the control signal is rising, logical ‘‘1’’, the constant value is connected to the comparator block instead of the output of the PV_Signal_Generator. Therefore, connection of faulty PV signal is avoided using the MUX block. The Altera DE0-Nano board consists of an ADC128S022 that is an eight channel 12-bit analog to digital converter (ADC). The rate of this ADC is adjustable from 50 Kbps to 200 Kbps. Thus, digital clock input of the ADC (SCLK) must be set to 800 Hz and 3.2 MHz. In order to operate at these frequencies, the control block of the ADC must consist of the clock divider unit. Because the main

oscillator unit is defined as clk in Fig. 16 and Fig. 17, it can only generate a clock signal with 50 MHz frequency. In the developed system, the frequency is 2 MHz; ADC provides conversion throughput rates of 125 Kbps. Eqs. (1)–(3) demonstrate this example, in which; T (data transfer rate); sps (sample per second); dt (detection time) and spdt (sample per detection time). By Eq. (3), the time is calculated to determine the voltage rise from 311 V to 357 V. There are 205 samples between 311 V and 357 V when the clock frequency of ADC is 2 MHz. The instantaneous voltage rise must be distinguished in this case so that the definite sample number defines a threshold constant. Namely, if the peak voltage of the signal suddenly rises and the total counted sample number does not reach 205, the logical status of the control signal keeps it level. According to the user manual, chip select (CS) is held low during the conversion process. Fig. 16 shows the output of ADC, which is presented as input_signal is used to detect the fault condition by forcing a voltage to drift from up to down.

T¼

Clock Freq 2  106 ¼ ¼ 125 Ksps 16 16

Fig. 11. Developed Electronic Measurement Card (EMC).

Circuit Breakers CB_inverter

CB_load

CB_grid Trigger Signals (0-5 V)

Defined Reference Threshold Values

Digital Outputs of FPGA

Developed Islanding Detection and Control Software with Quartus

FPGA Board FPGA Board

VLSI Design

Analog to Digital Converter (ADC128S022) Converted Electrical Signals to 0-10 V

Developed Electronic Measurement Card-1 Iinv, Vinv

Output of the PV Inverter

I, V, P, f and cosφ

Analog Inputs of FPGA

Converted Electrical Signals to 0-10 V

Developed Electronic Measurement Card-2

Converted Electrical Signals to 0-10 V

Developed Electronic Measurement Card-3

Igrid, Vgrid

Electrical Grid

Iload, Vload

Electrical Load

Fig. 10. The general schematic of the proposed control system.

ð1Þ

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G. Bayrak / Energy Conversion and Management 96 (2015) 228–241

Fig. 12. The implemented voltage measurement circuit.

Fig. 13. The general structure of the developed software.

Table 3 Selected grid threshold values in the experimental system.

12

Selected threshold values

Experimental

IEEE 929–2000

Over voltage Under voltage Nominal voltage Over frequency Under frequency

253 V (rms) 195 V (rms) 220 V (rms) 50.2 Hz 49.8 Hz

253 V (rms) 195 V (rms) 220 V (rms) 59.3 Hz 60.5 Hz

sps ¼

125; 000 ¼ 2500 50

ð2Þ

Control Signal

Counter & Control

12

dt ¼

20ms  4

360

Big_Constant

Comparator

311 ¼ 357  sinð2p50tÞ   1 311 sin  20 ms 357

Small_Constant

Comparator

12 ADC

¼ 1:633 ms

spdt ¼ 125 Kbps  1:633 ms ¼ 204:125 ) must be 205

ð3Þ ð4Þ

Fig. 14. VLSI based control system.

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G. Bayrak / Energy Conversion and Management 96 (2015) 228–241 12

Small_Constant

Comparator

Control Signal

Counter & Control

12

Big_Constant

Comparator

12

Constant

12

12

Inverter Output Signal (Digital)

Fig. 15. Modeling of the overall system.

ADC INPUT VCC INPUT VCC

clk DOUT

clk

SCLK

OUTPUT

SCLK

CS

OUTPUT

CS

OUTPUT

input_signal[11..0]

DOUT input_signal[11..0] inst

Fig. 16. ADC control block.

Control_Block clk

PIN_R8 DOUT PIN_A9

INPUT VCC INPUT VCC

clk DOUT

SCLK

OUTPUT

CS

OUTPUT

CS

OUTPUT

Control_Signal

Control_Signal inst1

SCLK

PIN_B14 PIN_A10 PIN_B12

Fig. 17. FPGA based control block.

Fig. 17 illustrates the control block, consisting of ADC_block, counter, comparator and clock divider. The system was performed by using very high speed integrated circuit hardware description language (VHDL) and schematic algorithm. Under voltage failure, Control_Signal is held; logical ‘0’ to activate circuit breaker. 5. Experimental study and results This section introduces the grid-tied prototype PV system constituted in the laboratory and the obtained results from the proposed FPGA-based islanding detection system. 5.1. Implementation of the proposed system in the laboratory The selected FPGA board controls the output of the inverter, the load and the grid parts of the PV system. Unlike other islanding detection methods, the proposed method monitors all sides of the PV system, thus it is independent of local load and NDZ which is the most important problem of islanding detection methods. Electronic Measurement Cards (EMCs) obtain the parameters such as voltage, current and frequency from the developed PV system. These parameters are converted to 0–10 V analog control signals suitable for a real-time control system for feeding them to the analog inputs of the FPGA board.

In general, the developed grid-tied PV system consists of four main units; a PV array, a DC/DC converter, an inverter, and the electrical load. Fig. 18 shows the developed PV-based DG system. Islanding detection of the PV system was investigated by creating an islanding detection test bench in the laboratory after setting up the grid-tied PV system. The advanced test bench for islanding detection shown in Fig. 19 consists of EMCs, solid state relays as circuit breakers (CBs) and an FPGA board for monitoring and managing the system. Analog outputs of the EMCs drive the analog inputs on the FPGA board. Obtained parameters were determined by developing antiislanding detection software using the FPGA board and its useful tools. The proposed method is easily implemented and low cost because of this structure. Fig. 19 also shows the EMCs and circuit breakers. The developed FPGA-based application software monitors the detection parameters of the PV system. There are three circuit breakers in the system. Voltages and frequency of the system are monitored continuously by the PV system. These breakers are switched to control the PV system. Fig. 19 shows the developed electronic measurement cards indicated as A, B and C. EMCs and circuit breakers can be easily implemented in designed system. The implemented controller system requires minimal hardware. The proposed method is not inverter resident, so it provides a robust and reliable solution for the subject.

G. Bayrak / Energy Conversion and Management 96 (2015) 228–241

237

Fig. 18. Photovoltaic power generating system.

Fig. 19. Developed islanding detection test system in the laboratory.

Fig. 20 also shows the FPGA-based control with an Altera DE0-Nano board. 5.2. Experimental results The proposed islanding detection algorithm detects the differences in threshold values of the grid voltage and the grid frequency. In this structure, voltages, current, and frequency values of the grid, load and inverter output are measured. The FPGA board continuously controls the threshold values in real time. Table 3 shows the selected grid threshold values for this experimental study. 5.2.1. Normal operation of the developed microgrid The developed software detects the variations in threshold values of the grid voltage and the grid frequency. In this arrangement, first of all currents, voltages, active power and frequency values of the grid, load and inverter output are measured. Threshold values continuously are controlled in real-time. If the threshold values are over/under selected threshold values, control system waits for two cycles to check the islanding situation. Then a trigger signal is generated for opening circuit breakers where connected grid, load, and inverter output sides. Fig. 21 shows both the normal operation of the PV system and the islanding situation for over voltage condition. The red line is the control signal of the circuit breaker, and the blue line is the voltage change of the system. The control signal is zero in a normal operation, and it is triggired by the control system in an islanding condition indicated in Fig. 21. 5.2.2. Operating the microgrid in an islanding condition By Eq. (3), the time is calculated to determine the voltage rise from 311 V to 357 V. There are 205 samples between 311 V and 357 V when the clock frequency of ADC is 2 MHz. The instantaneous voltage rise must be distinguished in this case so that the definite sample number defines a threshold constant. Namely, if the peak voltage of the signal suddenly rises and the total counted

sample number does not reach 205, the logical status of the control signal keeps it level. Over/under-voltage threshold values of the PV system are also determined by the developed FPGA-based software. When the grid voltage is over the defined threshold value (253 V) or under a specified threshold value (195 V), the control system waits for checking the islanding condition. Then, a trigger signal is sent to the circuit breakers by the FPGA board, and islanding is detected. If threshold values are over/under selected threshold values, the control system waits for 205 samples (defines the over voltage threshold value) to check the islanding condition, and then a trigger signal is generated to open circuit breakers. 5.2.2.1. Under/over voltage operation of the developed microgrid. The developed islanding detection process continuously evaluates feedback from the PV system and controls all of the systems. When islanding occurs, circuit breakers are switched immediately, and the PV system is disconnected from the grid. In the application, the grid voltage increases to 253 V; the control system waits for 205 samples to check the islanding condition, and then a trip signal triggers the circuit breakers. Fig. 22 shows the over voltage condition. The circuit breaker of the grid (CB_grid) and the circuit breaker of the inverter output (CB_inverter) are triggered by control signals from the FPGA board. These circuit breakers disconnect the PV system from the grid. When the grid voltage decreases to 195 V, the control system waits for 205 samples to check the islanding condition, and then a trip signal triggers the circuit breakers. Fig. 23 shows the under voltage condition. 5.2.2.2. Under/over-frequency operation of the developed microgrid. Fig. 24 illustrates the clock signal, the control signal, the square signal (output of comparator) and the output of the inverter. The period decreases from 20 ms (millisecond) to 18.4 ms (over frequency condition) in the last period of the signal, thus activating the breaker and disconnecting the PV system from

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Fig. 20. FPGA board used in the experimental study.

Fig. 21. (a) The normal and (b) the islanding mode of operations.

Fig. 22. Islanding detection for over voltage condition.

Fig. 23. Islanding detection for under voltage condition.

G. Bayrak / Energy Conversion and Management 96 (2015) 228–241

the grid. These simulation results demonstrate that the proposed method presents a simple, suitable and non-complex solution to islanding detection.

to detect islanding in this condition, and these values were selected for indicating the success detecting of the proposed system.

1

1

x0 ¼ pffiffiffiffiffiffi ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ¼ 50 Hz 5.2.2.3. Operating the microgrid in a resonance condition. In the experimental study, electrical load specification was selected as R = 300 O, L = 1,6 mH, and C = 2,5 mF. This load defines a 50 Hz grid frequency which equals the resonance frequency, and it is the worst scenario to detect islanding. Especially passive methods fail

239

LC

0; 16  2; 5 mF

ð5Þ

These parameters define a resonance condition, which is the worst scenario for islanding detection. Active powers of the load and the grid were selected equally to match the active powers. The active power mismatch is zero, and the system is in a

Fig. 24. The clock signal, the control signal, the square signal and the output of the inverter for over frequency condition.

Fig. 25. Clock signal, the control signal, and the output current signal of the inverter.

Fig. 26. Islanding detection time for developed FPGA-based control system.

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resonance condition. This condition is the worst operational scenario for islanding detection. Fig. 25 shows the clock signal, the control signal, and the output current signal of the inverter in the developed software with Quartus. The system detects islanding in 1.65 ms and then waits for 205 samples for checking the fault. Fig. 26 shows this situation. Circuit breakers clear the fault within two cycles under this load condition. Islanding detection time is only 1.65 ms in the proposed method. All detection and fault clearing times are considerable according to IEEE 929–2000. The PV system is not connected to the grid, and the proposed method is independent of the load and the inverter. As described by Eqs. (3) and (4), Fig. 26 illustrates that the detection time of the FPGA control board and the time chart of the control signal, which is generated by a VLSI-based modeled circuit. The detection time (1.65 ms), which is between 53.51 ms and 51.86 ms, is clearly shown in Fig. 26. 6. Conclusions In this study, a new remote islanding detection method was developed for PV-based DG systems. The developed method is a remote method that controls the load, grid and the output of the inverter with the communication of circuit breakers. A real-time controller with an FPGA detects the islanding condition. Remote islanding detection methods have the best performance, according to the passive and active methods. The proposed algorithm is independent of local load and inverter because it uses many parameters to detect islanding instead of measuring only the PCC voltage. Thus, the proposed method is not a passive method having NDZ changing by local load, and it is a communication based (coordination of the circuit breakers) method with no NDZ. In the study, the proposed method has a new remote method by using communication and control of the circuit breakers. The power quality does not change (because these methods are independent of local load and, they do not fail in a resonance condition), NDZ is zero, and the system is stable. There is no NDZ problem with this method because it checks all of the system parameters in real time, and it proposes a communication based method by using communication and control of the circuit breakers. The goal of the study also chooses a remote detection method to prevent the NDZ and, local load problems existing in passive and active detection methods. Islanding is detected by using an FPGA-based control and detection system when the frequency and voltages at three sides of the PV system exceed the allowable threshold values. The proposed method, continuously monitors the load, inverter and grid sides of the DG system, unlike conventional methods. The proposed algorithm also controls the frequency, active power, and reactive power in addition to the currents, so it is reliable to detect islanding. The islanding detection algorithm uses a low-cost Altera DE0-Nano board. This frequency is important for the immediate detection of grid failure and the generation of fault signals faster than conventional methods. The proposed method was verified by the development of a prototype PV system constituted in the laboratory. The obtained experimental results show that the proposed method is reliable, low-cost and independent of the load and the inverter. The islanding detection time is 1.65 ms even in a worst operational scenario as indicated by experimental results. The islanding detection time has a significantly shorter response time according to existing standards. Islanding detection time and the grid opening time is two cycles even in a resonance condition. The proposed method is efficient and presents a realistic solution to islanding. This method is also easy to implement and is suitable for real system applications in PV-based DG systems.

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