Comparative analysis of MPPT techniques for PV applications

The availability of solar energy varies widely with ambient temperature and different atmospheric conditions and hence the maximum power point (MPP) of photovoltaic system (PV) system is not stable. Therefore, a maximum power point tracking (MPPT) controllers are needed to operate the PV at its MPP.

Project Title

Comparative analysis of MPPT techniques for PV applications

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

The availability of solar energy varies widely with ambient temperature and different atmospheric conditions and hence the maximum power point (MPP) of photovoltaic system (PV) system is not stable. Therefore, a maximum power point tracking (MPPT) controllers are needed to operate the PV at its MPP. This work presents an evaluation of four different MPPT techniques for PV system such as perturb and observation (P&O), incremental conductance (INC), fuzzy logic controller (FLC), and genetic algorithm (GA). These MPPT techniques are implemented in an interleaved soft switching boosts converter (ISSBC) and performance comparison is made for these four MPPT algorithms in terms of parameters like global peak, tracking speed and power extraction. These algorithms are methodically investigated by means of simulation and a projected efficiency estimate method of experimentation. The

Project Objectives

The objective of this project is to compare and analyze different MPPT algorithms through simulation. For this purpose, initially a mathematical model of PV panel (based on characteristics were verified with respect to the industrial datasheet of KC200GT. Further, four different MPPT techniques were reviewed, namely, Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC) and Artificial Neural Network (ANN). All these four techniques were simulated in MATLAB-simulink environment. Then, all the techniques were fed with same irradiance variation and the techniques were simulated, analyzed and compared. MATLAB-simulink environment was used for developing all the models and carrying out all calculations

Project Implementation Method

The configuration for the proposed system is designed and simulated using MATLAB/simulink and implemented in 16F877A microcontroller. The proposed GA algorithm shows good dynamic performance to track the MPP of the PV even under the rapid change of the irradiation and cell temperature. The ISSB converter can be more efficient than the conventional converter; simple hardware design gives maximum efficiency at full load condition. The ISSBC with GA can provide the overall efficiency of about 98% which is higher than other algorithms due to decreasing the frequency of operation and switching losses and the response time is also less as compared to other algorithms.

Benefits of the Project

Renewable energy systems are becoming an important part of world’s energy. In the view of green house gas emissions and various adverse effects of other energy sources, solar photovoltaic (PV) energy has proven its importance amongst various other renewable energy sources. But the characteristics of PV array are non linear and time varying, thus the power generated changes continuously with atmospheric conditions. Thus maximum power point tracking (MPPT) algorithms are required for extraction of effective energy from PV array. This paper focuses on an investigation of various MPPT algorithms namely Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC) and Artificial Neural Network (ANN), for PV array installed for domestic application in stand-alone mode. These algorithms are compared on the basis of the tracking time, irradiance variation and operating point operations. The paper thus presents advantages, disadvantages and characteristics of diffe

Technical Details of Final Deliverable

The simulation results are verified experimentally using 16F877A microcontroller. The ISSB converter, 16F877A microcontroller, serial port MA232, digital oscilloscope and rheostat is used as DC resistive load. The P&O, IC, Fuzzy, and GA techniques microcontroller program is developed to track the MPPT. The proposed system is tested in laboratory and the photograph of the experimental setup that includes the 16F877A microcontroller is shown in Fig. 10. The solar panel is not shown in photograph. The switching frequency of ISSBC is 30 kHz. The controller program are scaled down and fusing into 16F877A microcontroller and generate gating signals to the ISSB converter. The MPPTs algorithm extracted power can be observed an exposition of approximately 04:00 hrs range from 09:00 hrs to 14:00 hrs with different PV insolation and cell temperature. Actually, experiment measurement obtained from different MPPT algorithm conducted on six different sunny days. The availed insolation, temperature and different climate pattern for experimental condition is tabulated in Tab. 4 at consign intervals of time; observe the output power as shown in Tab. 5. The output power values of P&O, IC, Fuzzy, and GA are 106.80, 108.40, 107.80, and 116.60 watts at case 7, corresponding energy comparison bar chart as shown in Fig. 11. From observed experimental result tabulation GA algorithm extract global maximum power recovery especially when solar panel different irradiation. In addition, the GA algorithm less transient, quick steady state response and efficiency compare to the rest of all other algorithm.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Affordable and Clean Energy

Required Resources

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