**4. MPPT results and discussion**

The developed fuzzy logic controller has been tested and simulated in MATLAB environment, and the fuzzy controller performance under various weather conditions such as variable irradiance (1000, 750, 500 and 250 W/m2 ) and temperature (20, 25, 30, 32 and 35°C) was analysed. The simulated results are analysed in the above conditions. **Figure 11** represented PV boost converter output voltage at various irradiance. **Figure 12** represented PV boost

converter output current at various irradiance. **Figure 13** represented PV boost converter output power at various irradiance. The fuzzy controller output signal of boost converter duty cycle is analysed at various weather conditions shown in **Figure 14**. The proposed MPPT system has been analysed in two different cases such as Case 1 (constant temperature and

**Figure 12.** Fuzzy-based 20 kW PV system output current at various irradiance.

Fuzzy Controller-Based MPPT of PV Power System http://dx.doi.org/10.5772/intechopen.80065 67

**Figure 13.** Fuzzy-based 20 kW PV system output power at various irradiance.

**Figure 14.** Duty cycle generation at various weather conditions.

**Figure 11.** Fuzzy-based 20 kW PV system output voltage at various irradiance.

#### Fuzzy Controller-Based MPPT of PV Power System http://dx.doi.org/10.5772/intechopen.80065 67

**Figure 12.** Fuzzy-based 20 kW PV system output current at various irradiance.

and current under various weather conditions as shown in **Figure 8**, and then the surface view of fuzzy rules is presented in **Figure 9**. The above designed fuzzy controller has been implemented in MATLAB simulation of 20 kW PV system and its boost converter as shown

The developed fuzzy logic controller has been tested and simulated in MATLAB environment, and the fuzzy controller performance under various weather conditions such as vari-

analysed. The simulated results are analysed in the above conditions. **Figure 11** represented PV boost converter output voltage at various irradiance. **Figure 12** represented PV boost

) and temperature (20, 25, 30, 32 and 35°C) was

in **Figure 10**.

**4. MPPT results and discussion**

able irradiance (1000, 750, 500 and 250 W/m2

**Figure 11.** Fuzzy-based 20 kW PV system output voltage at various irradiance.

**Figure 10.** Fuzzy simulation model for MPPT of PV system.

66 Fuzzy Logic Based in Optimization Methods and Control Systems and Its Applications

**Figure 13.** Fuzzy-based 20 kW PV system output power at various irradiance.

**Figure 14.** Duty cycle generation at various weather conditions.

converter output current at various irradiance. **Figure 13** represented PV boost converter output power at various irradiance. The fuzzy controller output signal of boost converter duty cycle is analysed at various weather conditions shown in **Figure 14**. The proposed MPPT system has been analysed in two different cases such as Case 1 (constant temperature and

at various weather conditions with fuzzy-based MPPT system. The fuzzy-based energy management system is developed and tested under various power demands, and then operation of battery charging and discharging is analysed. Finally, the proposed objective of grid integration of PV system is simulated in MATLAB, and system performance under various operating conditions is analysed. The improvement of power quality simulation results is compared with 1547 standard and proves the effectiveness of the proposed

Fuzzy Controller-Based MPPT of PV Power System http://dx.doi.org/10.5772/intechopen.80065 69

[1] Kumar A, Chaudhary P, Rizwan M. Development of fuzzy logic based MPPT controller for PV system at varying meteorological parameters. In: 2015 Annual IEEE India

[2] Mishra S, Sekhar PC. TS fuzzy based adaptive perturb algorithm for MPPT of a grid connected single stage three phase VSC interfaced PV generating system. In: 2012 IEEE

[3] Al Nabulsi A, Dhaouadi R. Efficiency optimization of a DSP-based standalone PV system using fuzzy logic and dual-MPPT control. IEEE Transactions on Industrial Informatics.

[4] Xie W, Hui J. MPPT for PV system based on a novel fuzzy control strategy. In: 2010 International Conference on Digital Manufacturing & Automation; ChangSha; 2010.

[5] Anandhakumar G, Venkateshkumar M, Shankar P. Intelligent controller based MPPT method for the photovoltaic power system. In: 2013 International Conference on Human

[6] Indumathi R, Venkateshkumar M, Raghavan R. Integration of D-Statcom based photovoltaic cell power in low voltage power distribution grid. In: IEEE-International Conference on Advances in Engineering, Science and Management (ICAESM-2012);

Power and Energy Society General Meeting; San Diego, CA; 2012. pp. 1-7

system.

**Author details**

**References**

2012;**8**(3):573-584

pp. 960-963

M. Venkateshkumar1,2\*

\*Address all correspondence to: venkatmme@ieee.org

2 Department of EEE, AVIT, Chennai, Tamil Nadu, India

Conference (INDICON); New Delhi; 2015. pp. 1-6

Computer Interactions (ICHCI); Chennai; 2013. pp. 1-6

Nagapattinam, Tamil Nadu; 2012. pp. 460-465

1 IEEE Young Professional, Madras Section, India

**Figure 15.** Analysis of the PV system performance at constant temperature.

**Figure 16.** Analysis of the PV system performance at constant irradiance.

variable irradiance shown in **Figure 15**) and Case 2 (constant irradiance and variable temperature shown in **Figure 16**).

### **5. Conclusion**

This paper deals with grid integration of PV power system with intelligent controllerbased energy management to improve the power quality. The above objectives are achieved by modelling of mathematical design of PV system and simulating PV system at various weather conditions with fuzzy-based MPPT system. The fuzzy-based energy management system is developed and tested under various power demands, and then operation of battery charging and discharging is analysed. Finally, the proposed objective of grid integration of PV system is simulated in MATLAB, and system performance under various operating conditions is analysed. The improvement of power quality simulation results is compared with 1547 standard and proves the effectiveness of the proposed system.
