CHAPTER 7 MAXIMUM POWER POINT TRACKING USING HILL CLIMBING ALGORITHM

100 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

101 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

102 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. P (Watt) Max.Power Point (Slope is Zero) Slope =ΔP/ Δv V (Volt) 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

103 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. PV Array Single Phase Inverter Transformer Output AC Gate Pulses Voltage and Current Sensing PWM Generation and Driving Circuits Modulation index Control unit for Implementing Hill Climbing Algorithm Figure 7.2 Block Diagram of Entire System

104 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.

105 Start Measure voltage and current Initialize modulation index (m) Power ( Pin ) = voltage * current Increases the m Measure voltage and current input Power (P fin ) = voltage * current If P in >P fin If P in =P fin If P in < P fin m = m+1 m = m m = m-1 Figure 7.3 Flow Chart for Calculating Modulation Index Value

106 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: Step 2: Step 3: Step 4: Step 5: Step 6: Step 7: Sensing and measuring the voltage and current of PV array Initialize the modulation index to a particular value The initial power P in is calculated Increase the value of m Sense the PV array voltage and current Calculate the modified power P fin 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.

107 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

108 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). V ac Vdc m * (7.1) 2 where m is modulation index, the ratio of amplitude of sine wave to triangular V dc is the dc supply given to inverter.

109 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

110 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.

111 Figure 7.8 Solar Panel (18 12=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 (18 12 = 216 cells) S.No. Parameter Value 1 Open circuit voltage (V oc ) 62.8 V dc 2 Peak voltage (V p ) 50.7 V dc 3 Short circuit current (I sc ) 6.4 A dc 4 Peak current (I p ) 5.8 A dc 5 Peak power (P p ) 295 W Based on the specifications of the PV panel rating listed in Table 7.2 the control circuit parameters are designed.

112 7.6.1 Control Circuit Figure 7.9 Control Circuit of the PV System

113 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). V vo R2 * V ( R R ) 1 2 s (7.2) where V s = Output from solar panel in volts V vo = Voltage proportional to output voltage from solar panel in volts R 1,R 2 = 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).

114 V io I s 3 5 * 75*10 * ( 1) (7.3) 10 R R 4 where I s = Output current from solar panel in ampere V io = Voltage proportional to output current from solar panel in volts R 5, R 4 = 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). A1 A2 A3 A4 A5 A6 A7 A8 Modulation index 5 * 2 4 8 16 32 64 128 256 (7.4) where A1 to A8 is MSB to LSB of digital modulation index

115 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.

Figure 7.10 Gate Pulse Generation Circuit 116

117 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

118 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

119 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.

120 Figure 7.14 Experimental Setup with 15W Lamp Load Figure 7.15 Experimental Setup with 60W Lamp Load

121 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

122 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.