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CHAPTER 7

MAXIMUM POWER POINT TRACKING USING

HILL CLIMBING ALGORITHM

7.1 INTRODUCTION

An efficient Photovoltaic system is implemented in any place with

minimum modifications. The PV energy conversion system implemented in

this thesis using neural network is trained for MPP depending upon the place

of installation. The system implemented using fuzzy logic requires prior

knowledge about the variation in geographical data. The hill climbing method

of MPPT implemented by Maheshappa et al (1998), dealt with increasing or

decreasing the array operating voltage and observing its impact on the array

output power. This algorithm is independent of place of installation and prior

study of the geographical data is not required. Any system implemented using

the hill climbing algorithm is considered to be most efficient system.

Noguchi et al (2000) proposed a novel maximum-power-point

tracking (MPPT) method with a simple algorithm by using a short-current

pulse of the PV array to determine an optimum operating current for the

maximum output power. Here, the optimum operating current was

instantaneously determined by taking a product of the short-current pulse

amplitude and a parameter k because the optimum operating current was

exactly proportional to the short circuit current

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Nicola Femia et al (2005) proposed that optimization approach lies

in customization of the perturb and observe MPPT parameters to the dynamic

behaviour of the PV system. Kasa et al (2000) presented a perturbation and

observation method with a capacitor identifier for MPPT. The variation of

duty ratio was determined by considering its circuit parameters. The actual

capacitance of an electrolytic capacitor in parallel with the photovoltaic array

has 50% tolerance of its nominal value. Teulings et al (1993) presented a

digital hill-climbing control strategy combined with a bidirectional current

mode power cell that makes to get a regulated bus voltage topology, suitable

for space applications, by means of two converters. MOSFET-based power

conditioning unit (PCU) along with a control algorithm to track the maximum

power point was discussed. Maximum power from each PV array was

extracted in spite of mismatch in the array characteristics. When the variation

of duty ratio was determined based on its nominal value, the performance of

the MPPT was degraded.

7.2 HILL CLIMBING ALGORITHM

The hill climbing algorithm locates the maximum power point by

relating changes in the power to changes in the control variable used to

control the array. This system includes the perturb and absorb algorithm

which was proposed by Xiao et al (2004).

Hill-climbing algorithm involves a perturbation in the duty ratio of

the power inverter. In the case of a PV array connected to a system,

perturbing the duty ratio of power inverter perturbs the PV array current and

consequently perturbs the PV array voltage. Figure 7.1 shows the

characteristic of PV array curve. In this method, by incrementing the voltage,

the power increases when operating on the left of the MPP and decreases the

power when on the right of the MPP. Therefore, if there is an increase in

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power, the subsequent perturbation is kept at same point to reach the MPP and

if there is a decrease in power, the perturbation is reversed. This algorithm is

summarized in Table 7.1. The process is repeated periodically until the MPP

is reached. The system then oscillates about the MPP. The oscillation is

minimized by reducing the perturbation step size.

Figure 7.1 Characteristic PV Array Power Curve

Table 7.1 Summary of Hill Climbing Algorithm

Perturbation Change in Power Next Perturbation

Positive Positive Positive

Positive Negative Negative

Negative Positive Negative

Negative Negative Positive

V (Volt)

Max.Power Point (Slope is Zero)

Slope =ΔP/ Δv

P (Watt)

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7.3 BLOCK DIAGRAM OF THE PROPOSED SYSTEM

Figure 7.2 shows the entire block diagram of the proposed system.

In this, the PV array output vary with temperature, insolation, angle of

incidence and the PV characteristics of the PV cell or array which is used. So

in order to track the maximum power point for a particular condition, the

voltage and current is sensed and is scaled to 5V through an operational

amplifier and is given as an input to the analog channel of the PIC

microcontroller for making necessary control action. The PIC microcontroller

tracks the variation of dp/dv which is either positive, negative or zero. If it is

zero, it doesn’t make any change in control signal. Whereas if it is positive, it

increments the modulation index and if it is negative, it decrements the

modulation index. The PIC microcontroller sends necessary signal to PWM

generator which generates gate pulses for triggering the inverter.

Figure 7.2 Block Diagram of Entire System

Output AC

PV Array

Single Phase

Inverter

Transformer

Control unit for Implementing Hill

Climbing Algorithm

PWM Generation and Driving Circuits

Modulation index

Voltage and

Current Sensing

Gate Pulses

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Chihchiang Hua et al (1998) proposed to track, the maximum

power point of the PV panel in real time using a simple algorithm based on

perturbation and observation (P&O) method which was widely used because

of its simple feed back structure and fewer parameters. Nobuyuki Kasa et al

(2005) proposed the digital signal processing kit to control power

conditioning unit and MPPT including the PV current and pulse width

modulation calculation. Figure 7.3 shows the flow chart of the implemented

algorithm by measuring the array voltage and array current information. The

PV array output is calculated and compared to the previous PV array output

power. Initially the modulation index (m) value is set and if the final output

power is equal to the initially measured output power, the control circuit

maintains the same m value. If it is greater, then m value is increased and

vice versa.

Eftichios Koutroulis et al (2001), proposed a simple method in

which the PV array output power delivered to a load was maximized using

MPPT control systems, in which the control unit drive the power conditioner

such that it extracted the maximum power from a PV array. In this method, a

Buck-type dc/dc converter was used where the duty cycle variation was not

analysed. To overcome this, PWM technique is implemented to switch on the

inverter circuit.

The level of power flow depends on the desired array voltage value

determined by the MPPT algorithm. There are two possible situations that

need to be addressed. First, an increase in the array voltage is required, and

secondly, a decrease is required. The voltage output of the voltage source

inverter (VSI) is fixed, the power flow is varied by altering the VSI output

current. If the MPPT algorithm requires a decrease in the array voltage, the

output current is increased in phase with the grid voltage to a stable

magnitude determined by modulation index using PWM generator.

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Figure 7.3 Flow Chart for Calculating Modulation Index Value

Start

Measure voltage and current

Initialize modulation index (m)

Power (Pin) = voltage * current

Increases the m

Measure voltage and current input

Power (Pfin) = voltage * current

If Pin =Pfin

If Pin < Pfin

If Pin >Pfin

m = m+1 m = m-1 m = m

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This causes an increase in the positive power flow towards the load.

The extra power comes from the array, which causes the array voltage to fall

to the desired value as suggested by Krein et al (2003). The desired voltage is

reached, the output current goes down to a level that the power on the array

and load are equal once again. If an increase in the array voltage is required,

the opposite effect occurs by which a constant voltage is maintained.

Algorithm and flow chart:

The algorithm used for MPPT is discussed below:

Step 1: Sensing and measuring the voltage and current of PV

array

Step 2: Initialize the modulation index to a particular value

Step 3: The initial power Pin is calculated

Step 4: Increase the value of m

Step 5: Sense the PV array voltage and current

Step 6: Calculate the modified power Pfin

Step 7: If the change in power is positive, increase m value; if it

is negative, decrease m value’ and if there is no change

in power, m value is retained.

Step 8: Repeat step 5.

The above algorithm for MPPT is incorporated in PIC

microcontroller 18F452 using MPLAB IDE.

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7.4 SIMULATION MODEL

Figure 7.4 shows the simulation model of the proposed system. The

input parameters from the PV array are sensed through hill climbing block.

According to the variations in the PV array parameters, the corresponding

modulation index (m) value is obtained. Salas et al (2006) implemented a new

algorithm for MPPT. The algorithm was programmed in a PIC

microcontroller and according to the panel input parameters, the duty cycle is

varied in order to track the maximum power output. Based on this technique

in this proposed work, the m value is varied using hill climbing algorithm and

the corresponding PWM pulses are produced to trigger the inverter.

Figure 7.4 Simulation Model of the PV System Using Hill Climbing

Algorithm

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Figure 7.5 shows the simulation block of hill climbing algorithm.

The input parameters current and voltage is sensed from the PV panel. Any

positive change in power indicates increase in m value; and any negative

change in power indicates decrease in m value’ and no change in power

indicates to retain the m value.

Figure 7.5 Hill Climbing Simulation Block

Based on the variation in m value obtained using hill climbing

algorithm, the corresponding gate pulses are produced in the PWM circuit.

These pulses are used to trigger the MOSFET used in the inverter circuit. The

output voltage generated by the inverter is given by the equation (7.1).

*2dc

acVV m (7.1)

where m is modulation index, the ratio of amplitude of sine wave to

triangular

Vdc is the dc supply given to inverter.

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7.5 SIMULATION RESULTS

The bridge inverter circuit requires four gate pulses in order to

trigger the MOSFET. The first two pulses for one arm of the inverter bridge

are generated by comparing the triangular and the zero phase shifted sine

wave such that each pulse is a complement of the other. In the similar way

pulses for the second arm is generated by comparing the triangular wave and

180 degree phase shifted sine wave as suggested by Krein et al (2004).

The variation in the modulation index given to the PWM generation

generates gate pulses to trigger the inverter and produces a constant output.

Figure 7.6 shows the output waveform of PWM generator. In this, the gate

pulses G1, G2, G3 and G4 are given to the corresponding MOSFETS T1, T2,

T3 and T4 respectively.

Figure 7.6 Gate Pulse output

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The variation in the modulation index given to the PWM generation

generates gate pulses to trigger the inverter and produces a constant output.

The gate pulses G1, G2, G3 and G4 are given to the corresponding

MOSFETS T1, T2, T3 and T4 respectively. Figure 7.7 represents the inverter

output current and voltage waveforms.

Figure 7.7 Inverter Output Current and Voltage Waveform

7.6 HARDWARE IMPLEMENTATION

The hardware is implemented using hill climbing algorithm for

tracking the maximum power from the solar panel. Figure 7.8 shows the solar

panel used for this work. The output of the panel namely voltage and current

is sensed and given to the PIC microcontroller for determining the variation in

power. The hill climbing algorithm for traction of maximum power point

depending on variation in solar intensity is implemented using this

microcontroller.

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Figure 7.8 Solar Panel (1812=216 cells)

The first requirement in designing the hardware is solar panel and

its specifications. The specification of the panel used is represented in the

Table 7.2. It indicates the rating of open circuit voltage, short circuit current,

peak power delivered by the panel, etc.

Table 7.2 Solar Panel Specification (1812 = 216 cells)

S.No. Parameter Value

1 Open circuit voltage (Voc) 62.8 V dc

2 Peak voltage (Vp) 50.7 V dc

3 Short circuit current (Isc) 6.4 A dc

4 Peak current (Ip) 5.8 A dc

5 Peak power (Pp) 295 W

Based on the specifications of the PV panel rating listed in

Table 7.2 the control circuit parameters are designed.

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7.6.1 Control Circuit

Figure 7.9 Control Circuit of the PV System

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7.6.1.1 Sensing Panel Parameters

The control circuit is shown in Figure 7.9. The panel parameters

like voltage and current are sensed and transferred as an input to the

microcontroller for determining the variation in power. The voltage is sensed

by a voltage divider circuit and the current is sensed using shunt.

7.6.1.2 Voltage sensing

The voltage divider circuit consists of resistances R1 and R2.The

output of the voltage divider is given by the equation (7.2).

2

1 2

*( )vo s

RV VR R

(7.2)

where Vs = Output from solar panel in volts

Vvo = Voltage proportional to output voltage from solar panel

in volts

R1,R2 = Resistances in ohms

The zener diode Z1 is used to limit the voltage input to the

microcontroller to 5V.

7.6.1.3 Current sensing

The dc current from the panel is sensed using a shunt which gives

the output of 75 mV when a current of 10A flows. The voltage obtained from

the shunt is five scaled using the operational amplifier connected in non

inverting mode. The output across the zener diode is given by the

equation (7.3).

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3 5

4

* 75*10 * ( 1)10

sio

I RVR

(7.3)

where Is = Output current from solar panel in ampere

Vio = Voltage proportional to output current from solar panel

in volts

R5, R4 = Resistances in ohms

7.6.1.4 Microcontroller Logic Circuit

The hill climbing algorithm for the traction of maximum power

point depending on variation in solar intensity is implemented using

microcontroller PIC18F452.

In this circuit, the reset switch is used to reset all the registers in the

microcontroller whenever it is necessary. The variation in voltage and current

is sensed and based on that, the modulation index value (m) is produced as an

eight bit digital output in the port B of the microcontroller.

7.6.1.5 Digital to Analog Converter

The output from the microcontroller is converted into analog form

using the digital to analog converter DAC 0808. The reference signal given to

the DAC is 5V .The output of the DAC is given by the equation (7.4).

1 2 3 4 5 6 7 85 *2 4 8 16 32 64 128 256A A A A A A A AModulation index

(7.4)

where A1 to A8 is MSB to LSB of digital modulation index

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7.6.1.6 Modulating signal generation

The modulating signal is used for the generation of inverter gate

signals. In order to maintain the output of the inverter as 50Hz, the signal is

tapped from the grid and stepped down to 5V. Then it is multiplied with the

modulation index using analog multiplier AD532 to get the required

modulating signal. The 6V signal generated from the transformer is converted

into 5V using operational amplifier U1 and U2. The resultant modulating

signal from the output of the multiplier is converted into two sinusoidal

signals each phase shifted by 180 degree.

7.6.1.7 Triangular carrier signal generation

The triangular wave is generated using the combination of

operational amplifier operated as a square wave generator and integrator.

7.6.2 Gate Pulse Generation Circuit

Figure 7.10 shows the gate pulse generating circuit. In this G1, G2,

G3 and G4 represents gate pulses and R1, R2, R3 and R4 represents the

respective references. The variation in the modulation index given to the

PWM generation generates gate pulses to trigger the inverter and produces a

constant output. The bridge inverter circuit requires four gate pulses in order

to trigger the MOSFET. The first two pulses for one arm of the inverter

bridge are generated by comparing the triangular and the zero phase shifted

sine wave obtained from the control circuit, such that each pulse is an

complement of the other. In the similar way pulses for the second arm is

generated by comparing the triangular wave and 180 degree phase shifted sine

wave. All the four pulses are then given to the opto-coupler MCT 2E which

act as an isolator to prevent the controlling circuit from the surges arising in

the inverter.

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Figure 7.10 Gate Pulse Generation Circuit

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Figure 7.11 shows the gate pulses generated in the gate pulse

generating circuit. The pulses G1, G2, G3, G4 are obtained using

oscilloscope. According to the variation in solar insolation the response of the

modulation index varies. Based on the change in m value the gate pulses

generated also varies its time duration. Gate pulses generated using simulation

model presented in Figure 7.7 matches with the hardware gate pulse

generation circuit waveforms.

Figure 7.11 Gate Pulses G1, G2, G3 and G4 given to the Inverter

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7.6.3 Inverter Circuit

The generated gate pulses from the driver circuit are connected to

the MOSFET IRF 640 which is connected in bridge configuration. The

snubber circuit is connected in parallel to all the four MOSFET in order to

avoid device damage due to surges. The inverter circuit is shown in the

Figure 7.12.

Figure 7.12 Inverter Circuit

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The output voltage waveform of the inverter is connected to the

step up transformer to obtain a constant secondary output voltage for a load of

15W lamp. The output of the inverter is connected to the primary side of the

step up transformer which is provided with tappings of 10V, 20V, 30V, 40V.

According to the inverters output the corresponding tappings are used in the

transformer in order to produce constant secondary voltage. Figure 7.13

shows the output voltage waveform of the inverter given to the primary of the

transformer and the step up voltage output given to the load.

Primary side Secondary side

Figure 7.13 Voltage Waveform of Inverter with 15W Lamp Load

Figures 7.14 and 7.15 shows the experimental setup for different

load conditions. Depending on the solar insolation, the control circuit PC

board senses and drives the gate pulse circuit which is given to the inverter

circuit. The output of the inverter is given to the suitable transformer tapping

in the primary side in order to produce a constant secondary output required

by the load.

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Figure 7.14 Experimental Setup with 15W Lamp Load

Figure 7.15 Experimental Setup with 60W Lamp Load

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Figures 7.16 and 7.17 shows the output waveform of array power

versus time and array current. The graph indicates the curve drawn for two

sets of datas – one with MPPT control and the other without MPPT control.

The graph drawn between the array power and time shows the difference in

variation in the power generated with MPPT and without MPPT during the

morning and evenings. By using the hill climbing algorithm, it is observed

that the amount of power produced by the PV generator trained using MPPT

follows the pattern of irradiance.

Figure 7.16 Output waveform of Array Power Vs Time

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Figure 7.17 Output Waveform of Array Power Vs Array Current

7.7 CONCLUSION

The panel is trained statically using hill climbing algorithm for

maximum radiation. It predicts the maximum power point voltage and the

modulation index value. The pulse width modulation scheme is used to trigger

the gate of the switching device, which reduces the lower order harmonics at

the output of the inverter. The simulation results match with the

implementation results. The implementation complexity of the system is low

compared to the above two algorithms. The main advantage is, the system is

not array dependent and periodic tuning is not required.