Development of Load Control Algorithm for PV Microgrid

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 7, No. 2, April 2017, pp. 619~630
ISSN: 2088-8708, DOI: 10.11591/ijece.v7i2.pp619-630  619
Journal homepage: http://iaesjournal.com/online/index.php/IJECE
Development of Load Control Algorithm for PV Microgrid
Mohamad Haireen Bin Fatheli1
, Nur Izzati Zolkifri2
, Chin Kim Gan3
, Musa Bin Yusup Lada4
1
Transmission and International Network Management, Telekom Malaysia, Malaysia
1,2,3,4
Faculty of Electrical Engineering, UniversitiTeknikal Malaysia Melaka, Malaysia
Article Info ABSTRACT
Article history:
Received Aug 18 , 2016
Revised Nov 24, 2016
Accepted Dec 10, 2016
The variability of solar irradiance caused by weather conditions could result
in the mismatch between the solar PV generation and demand, particularly in
the microgrid context. This may lead to detrimental effects of over/under
voltage or over/under frequency. In this regard, this paper presents the
laboratory setup of a grid-connected PV inverter operating in islanding
condition. To achieve this, a load control algorithm is proposed to provide
autonomous real time demand control that follows the PV generation to
maintain generation-demand equilibrium requirement. Laboratory results
show that the proposed load control algorithm is capable to address the
voltage and the frequency violation in islanding condition, regardless of the
variation of irradiance and power generated by the PV sources.
Keyword:
Demand response
Microgrid
Solar PV system
Copyright © 2017 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Chin Kim Gan,
Faculty of Electrical Engineering,
Universiti Teknikal Malaysia Melaka,
Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia.
Email: ckgan@utem.edu.my
1. INTRODUCTION
The demands forelectrical power these few years are increasing, which also see the increase of the
use of distributed generation (DG). Energy sources of DGs are divided into two, which are renewable and
fossil fuel energy. In order to minimize the utilization of oil and gas as the main source of power generation,
numerous researches and studies have been performed these recent years, concentrating on Renewable
Energy (RE) as an alternate generation.Renewable Energy Sources (RES), interfaced with power energy
conversion and integrated with the loads and energy storage system, enables the RES to serve as a Microgrid
that can work in a stand-alone or grid-connected mode operation [1], which makes the microgrid concept
become practical. Microgrid is defined as a system that comprises of distributed generation that is
interconnected with medium and low voltage distribution system for energy transfer to the grid in grid-
connected mode operation [2]. Microgrid offers mutual advantages in the context of the user and utility
service provider, while helping in preserving the environment through cleaner energy produced from the
RES, which is proven free from any environmental concern. From the user perspective, the establishment of
microgrid through the grid interface connection promises improvement on the network quality by providing
reactive and harmonic compensation [3], as well as reducing the impact of pollution to the environment and
the cost to the user through an incentive scheme introduced by the local energy commissions.
Photovoltaic (PV) generation is one of the popular renewable energies. Solar energy is inexhaustible
and effective to generate bulk supplies of electricity. However, PV generation type depends on the weather
condition, which implies the output power is not constant all the time. The introduction of PV grid-tie
inverter helps to overcome the constant output issue by providing integration of the PV power output with
utility in a grid system, compensating each other [4]. The role of grid-tie inverter is to convert the DC supply
or non-asynchronous supply into synchronous AC supply of voltages that could smoothly or easily

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Development of Load Control Algorithm for PV Microgrid (Mohamad Haireen Bin Fatheli)
620
interconnect with the utility supply [5]. Moreover, in grid interconnected mode, the inverter serves as a
current source to provide preset power to the grid [6].
PV grid-tie inverter is designed with an anti-islanding mode that prevents power from the inverter
being transmitted to the grid when the grid is disconnected. As a consequence, local load will be interrupted
indiscriminately, which incurs unnecessary outage following the grid outage [7]. Hence, the optimization of
energy is not fully utilized though the source is ready and available. The islanding offers a solution to this
problem through intentional islanding that allows the inverter to be working, supplying the power to the local
loads in this mode. However, the intentional islanding has a drawback, in which the solar energy fluctuates
over time, depending on the weather condition. Voltage and frequency in intentional islanding are risky in the
wake of the uncertainty of the PV supply. With regard to this, in this paper, a load control algorithm system
is presented in this paper, designed to address voltage and frequency stabilization issue, and further to
compensate the uncertain energy produced by the PV supply. The load control algorithm will serve as a load
management that follows generation, to provide protection to the local loads and PV system, respectively.
LABVIEW software has been incorporated with the Data Acquisition (DAQ) devices in this experiment to
measure the current and voltages of the PV and load system.
2. RESEARCH METHOD
2.1. Sunny Boy 2000 HF-US Grid-Tie PV Inverter
The Sunny Boy 2000 HFS-US is a PV inverter system which functions to convert direct current
(DC) of a PV array into alternating current (AC), to feed into the power distribution grid. The PV inverter
system operates on a load that resonates at 50Hz frequency, which matches the output of the PV inverter
perfectly. Due to the safety design, the Sunny Boy PV inverter is incorporates withan anti-islanding
protection algorithm system to prevent the PV inverter from transporting the supply when the grid is
disconnected. The Sunny Boy PV inverter will inject periodically both leading and lagging reactive current in
this anti-islanding algorithm to destabilize and de-energize from a balance islanding condition.
Although reconfiguration of the Sunny Boy PV inverter into the islanding is prevented
automatically in-system, it still can be configured to the islanding externally. The fundamental of the Sunny
Boy PV inverter operation is by having the load to resonate at 50 Hz frequency to match the PV inverter
output [8]. Injecting an external AC source with 50Hz frequency to the load until the source signal is
matched to the PV output will allow the Sunny Boy PV inverter to work in islanding mode. In this
experiment, reconfiguration into the islanding mode was conducted by isolating the grid supply manually. A
reference signal from the external source was injected to the PCC until the signal matched the output of the
Sunny Boy PV inverter. Then, the Sunny Boy PV inverter could be configured to an intentional islanding
mode [9].
2.2. Point of Common Coupling (PCC)
PCC in this experiment provided a common point for the PV inverter and utility supply to
synchronize. The PCC functioned as a base of the access point for direct measurement between these two
supplies. The PCC was designed with the circuit breaker protection, to prevent over-current fault from
damaging the system [10]. Terminal Blocks were attached to the DIN-Rail and mounted on the board to
provide accessibility to the source which was interfaced in the PCC. The PCC electrical diagram is shown in
Figure 1(a). The hardware implementation is shown in Figure 1(b).
(a) (b)
Figure 1. (a) PCC electrical diagram, (b) PCC hardware implementation

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2.3. Isolation Transformer
Isolation transformer was employed in this experiment to isolate the output neutral of the PV
inverter system from the voltage source supply, where the voltage source supply served as a reference signal
in intentional islanding mode. The PV inverter and reference voltage supply were merged together in the
PCC board in an intentional islanding environment. Whenever two sources merged together, there would be
twoneutral inputs and a single output neutral connection, as illustrated in Figure 2(a). This led to the problem
of how to connect a single output neutral, given with two inputs neutral at the same time.
Combining these two sources does not require their neutrals to be connected together. Connecting
the inputs neutral together to the output neutral can create circulating current between the input neutrals, as
shown in Figure 2(b), which can be hazardous if two inputs neutral come from the different sources. An
isolation transformer placed in series at one of the sources should provide the solution to this problem. The
isolation transformer serves as a medium to electrically separate one of the neutral input wires coming from
the two different sources. As a result, only one input neutral wire is connected to the output neutral wire
directly. In this experiment, neutral input from the voltage source was electrically separated using the
isolation transformer, which enabled the neutral input from the PV inverter system to be connected directly to
the output neutral to the load.
(a) (b)
Figure 2. (a) Two inputs neutral and a single output neutral, (b) Circulate current between inputs neutral
2.4. Load Bank
Constant load at 1000W single phase was set in this experiment with the intention to observe the
effects of the fluctuating PV supply to the constant loads. Three-phase load bank was utilized in this
experiment and the load was recalculated to be set in this load bank accordingly. This was because the load
required in this experiment should be in a single phase while the load bank utilized was a three phase load
system.
The load bank utilized in this experiment had a balance load whose phase impedances were equal in
magnitude and phase. The resistance value of the load bank is given in wattage (W). As the load was
balanced in a three-phase load bank, conversion of three-phase loadinto the single phase load was done as in
Equation 1:
Pload 1Ø (1)
2.5. Development of Load Control Algorithm Software
Development of a load control algorithm system is divided into two, which are software design, that
acts as a brain to the load control algorithm, and hardware implementation, that demonstrates the
effectiveness of the load algorithm. The algorithm flow chart is developed as guidance to the software
development. Figure 3 below shows the algorithm flow chart developed for this load control system.
The algorithm flowchart in Figure 3 starts with the measurement of the current from PV inveter and
the load system. The algorithm program is developed to activate subject to the PV energy availability and
will be placed to off immediately once the PV energy has diminished. Then, the PV current is compared to
the load current. If the PV current is higher than the load current and meets the time delay set at respective

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622
individual load, the load will be connected sequentially. However, if the PV current is lower than the current
load in turn, the algorithm flow chart will measure the difference between the load current and the PV
current, respectively. The difference of the value is then compared with the threshold value. If the difference
current is greater than the threshold value given, load will be shed accordingly, or else the amount of the load
will be retained as it has been connected. The algorithm is a continuous process as long as PV energy is
present. LABVIEW software is incorporated with the Data Acquisition (DAQ) devices to measure the
current and voltages of the PV and load system.
Figure 3. Algorithm flow chart for load control system
A single channel configuration with a complete load control algorithm system for the experimental
setup is shown in Figure 4. DAQ Assistant is utilized as a single simulated device to measure three
parameters in the live system, namely, PCC Voltage, PV current and load current, respectively. Select
Signals VI is employed in this software configuration to split up the three parameters measured using a single
DAQ Assistant.

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Figure 4. Single channel of load control algorithm system
The hardware devices for load control algorithm system are listed in Table 1, which include the
Point of Common Coupling (PCC) with the circuit breakers protection, isolation transformer, low voltage
(LV) step-down transformer, transducer, relay switching modules, National Instrument Data Acquisition (NI
DAQ), DC-DC converter, Buffer circuit, and LABVIEW programming,which all form a complete load
control algorithm system.
Figure 5 shows the load control algorithm block diagram established for this project.
Table 1. Hardware components for load control algorithm system
No. Hardware components Rating/Model Quantity
1 Isolation Transformer 240/240 V 1
2 LV step down transformer 240/6 V 1
3 Current Transducer 15 V, 20 A, LEM HY 20-P 2
4 Relay Switching Module 5V, 8-channel Relay Interface Board, 15-20mA Driver Current 2
5 Relay Switching Module 5V, 4-channel Relay Interface Board, 15-20mA Driver Current 1
6 NI compact DAQ Ethernet chassis NI 9181 4
7 Digital Output Module NI 9472 3
8 Analog Voltage Input Module NI 9205 1
9 NI Managed Ethernet Switch NI – MES 3980 1
10 Buffer Circuit 20 x1kΩ resistance circuit 1
11 DC-DC Converter 1A, 12/5 V 1
12 AC/DC Enclosed Switching Dual Power Supply 10A, 240Vac/12Vdc 1

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Figure 5. Load control algorithm block diagram
2.5.1. LABVIEW Software Load Control Algorithm
In this experiment, LABVIEW software was incorporated with the Data Acquisition (DAQ) devices
to measure the currents and voltages of the PV and load system. The measured parameters data were then
transferred to the control application design in the LABVIEW code, to process the inputs following the
designated algorithm software and generate digital output signals to trigger the relay function of a load
control system. LABVIEW software has two panel architectures, namely the front panel and the block
diagram panel. The front panel serves to define the algorithm interface, which in this experiment functioned
to monitor the software interface and measured parameters.
Figure 6 shows the front panel of the LABVIEW software.
Figure 6. Front panel of LABVIEW software
2.6. Experimental Setup
The actual experimental was carried out by configuring the PV inverter system operating in the
islanding mode. To ensure the transition of the grid connected to the islanding mode be successful, a load
bank was utilized to match the output generated by the PV system, while waiting the load algorithm system
to initiate. Otherwise, the transition would not be successful while conducting experiment at the peak output

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of the PV system. Figure 7 shows the hardware experimental setup. The novelty of this experimental setup is
that the configuration allows the grid-tie inverter to operate in islanding mode with the source of reference
voltage. For simplicity, we considered the utility as the reference voltage, which can be replaced by other
tupes of AC power source.
Figure 7. Hardware experimental setup
3. RESULTS AND ANALYSIS
3.1. Intentional - Islanding With the Load Control Algorithm System
The load control algorithm is a designated system that controls the amount of the load to be
connected corresponding to the PV generation level. The load control algorithm system monitors the
magnitude of current delivered to the load, and controls the energy balance between the PV generation and
load demand respectively.
3.1.1. Load Demand Follow the PV Generation
PV inverter current and load current are two parameters which were monitored and controlled in this
algorithm design. The load current was designed to follow the PV current, as shown in Figure 8. Load
demand parallel with generation was successfully established in the actual system test operating in islanding
mode, producing load current corresponding to PV current change.
The algorithm design managed to control the load amount according to the PV generation level by
controlling the load current which continuously followed the PV current all the time. However, at certain
operation cycle, it was found that the load current encountered fluctuation for a few seconds before resuming
normal operation. Fluctuations occurred due to the hardware timing of data acquisition (DAQ) that was not
synchronized with the software timing. Never the less, the fluctuation could be minimized by introducing
time delay to the software program.
As a result of the mismatch of the software and hardware timing, fluctuation occurred since the
relay switching module was supplied with intermittent signal from the DAQ modules. Furthermore, the DAQ
modules permitted the relay operation to intermittently operate until the mismatch between the software and
hardware timing was rectified through self synchronization on these two timings accordingly. The load
current was higher in the graph presented, as a sign to prevent reverse current from propagating into the
external voltage source. The load was slightly higher from the PV current designed in the algorithm as a
security assurance to prevent reverse power flow from occurring. Regardless of the intermittent of the PV
supply, the load could be controlled for the amount of the PV supply generated. Unlike microgrid
PV panel
Grid-tie Inverter
Distribution
Board
Point of Commo n
Coupling (PCC)
Isolation
Transformer
TNB single
phase supply
LABVIEW
monitoring and
controlling
Load control
Algorithm
Bulbs Load
Load Bank

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experimental setup using solar power emulator [11], actual working PV system with real connected loads was
considered in this work.
Figure 8. Load current follow PV current generation
3.1.2. Voltage Stability Offered by Load Control System
Figure 9 shows the load voltage measured in islanding mode with the load control algorithm system.
The voltage can be briefly described as with the load control system, the load voltage was observed operating
in +10%, -6% voltage limit [12] and free from any voltage violation in islanding.
Figure 9. Load voltage operating in islanding with load control system
Figure 10 shows irradiance as a variable parameter. The fluctuation of irradiance energy was due to
the weather and global sun position, which implies that the PV source is not a constant type of energy, thus
posing reliability issues in power generation [13].
The irradiance energy was then transformed into DC input of the PV inverter, where the energy
conversion output was in AC waveform, as shown in Figure 11. The AC voltage declined excessively at the
beginning of the operational cycle because the transition from grid was disconnected to the islanding mode.
Nevertheless, the DC voltage could be kept constant, mainly due to the Maximum Power Point Tracking
(MPPT) that maximized the power output in event of irradiance fluctuation.
The AC voltage successfully controlled working at voltage limit, free from any voltage violence. In
spite of fluctuation due to weather variances affecting the input PV inverter, which was unmanageable by the
MPPT, the voltage could still be retained as constant due to the aids of the load control algorithm system.
Hence, the PV inverter current source proves fit to workin islanding environment.
Fluctuation due to mismatch of hardware
and software timing

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Figure 10. Irradiance data
Figure 11. DC and AC voltage PV inverter system
3.1.3. Frequency Stability Offered by Load Control System
Figure 12 shows the load frequency showing with the load control algorithm system, in which
frequency was operated in limit from 49.5Hz to 50.5Hz [14] and immune from any gradual changes in the
course of unreliable source provided by the PV system in islanding.
Figure 12. Load frequency measured
Transition from grid
disconnected to island
mode

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3.2. PV Inverter Current Distortion
The measured PV inverter current and the load current are shown in Figure 13. It was observed that
the inverter current waveform was in a form of distorted signal, while the load current waveform was purely
in sinusoidal from.
The degree of distortion was due to the harmonic presence, showed when significant distorted signal
was encountered and when low PV supply was generated to the load. At this time, the PV inverter operated
with low power conversion where the distortion was very high [15] [16]. The external voltage source in turn,
provided the necessary current that mixed up with the distorted current from the PV inverter, producing pure
sinusoidal waveform to the load. Thus, power quality was preserved in good quality to the load.
Figure 13. PV inverter current and load current
Figure 14 shows the irradiance data against temperature, showing that distorted signal appeared at
low irradiance, proportional to the low panel temperature. The relation shows that when temperature rises,
the irradiance will rise as well [17]. As such, the inverter would have problems producing good power quality
if it had worked as a standalone system. The function of external voltage in this experiment was to ensure
good power quality be delivered to the load, providing compensation to the distorted signal at the time of the
irradiance energy being low.
Figure 14. Irradiance versus temperature
The results showed that the load current followed the PV current continuously all the time until the
PV supply was dismissed. The voltage was constantly stable at the point of PCC, as the load was connected
based on the PV generation level, which prevented any over-voltage or under-voltage scenario from

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occurring. Hence, the load control algorithm system, instead of addressing the stability issue in the
intentional islanding from the context of voltage and frequency, also provided protection from over-voltage
or under-voltage to the load and PV supply at the same time. It has been proven that the load control
algorithm system can effectively control the load in actual test of grid connected PV system for PV microgrid
restoration, which is in line with the objective of this paper.
4. CONCLUSION
Variability of solar irradiance due to weather condition could result in the mismatch between solar
PV generation and demand, particularly in the microgrid context. This may lead to detrimental effects of
over/under voltage or over/under frequency. As proven in this study, the developed load control algorithm is
able to accommodate PV generation operating in intentional-islanding mode. The load control algorithm
system will maintain demand-supply in a balance condition, by usinga switch relay control that connects the
loads according to the PV generation level. The load control algorithm system has been successfully designed
using LABVIEW software to form a complete and autonomous load control algorithm system to control the
load presence in accordance to the PV generation.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial support provided by the Ministry of Higher
Education Malaysia under the Research Grant: RAGS/1/2015/TK03/FKE/03/B00096. Special appreciation
and gratitude are expressed to the Center of Robotics and Industrial Automation (CeRIA), Centre of Research
and Innovation Management (CRIM) and Faculty of Electrical Engineering (FKE) ofUTeM for giving the
financial and moral support forsuccessful completion of this project.
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