Intelligent Control Based MPPT for Grid Penetration of Photovoltaic power System

International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 10 No.4 (2015) pp.3967-3973 © Research India Publications; http://www.ripublication.com/ijaer.htm

3967

Intelligent Control Based MPPT for Grid Penetration of Photovoltaic power System

M.Venkateshkumar1 Dr.R.Raghavan2

1Research scholar Sathyabama University 2Education Consultant

[email protected] [email protected] Abstract- Insufficiency of power generation due to lack of fossil fuel and lack of cost-effectiveness in rural areas have become a challenge to be solved in order to get better utilisation of people’s revenue source. The single solution to focus the use of renewable energy sources is to generate electricity with these sources during the generation shortage through other sources to meet the consumer demand. Operation of grid integration of photovoltaic power system is analysed and its performance under various weather conditions. The projected Fuzzy logic based MPPT, requires the sensing of the DC voltage output of PV panel and solar irradiation. The planned fuzzy control based maximum power point tracker (MPPT) has been simulated using MATLAB environment. The simulation results are evaluating the performance of the proposed model with changing solar irradiation conditions. The simulation results are compared with that of existing model for establishing the effectiveness of the proposed model Key words: Intelligent control, Fuzzy Logic, MPPT, Photovoltaic, MATLAB

I INTRODUCTION Because of the concern about the impact of CO2 and the anxiety on the effect of using fossil fuels based power generation technology on the environment, in recent years, the researchers are focusing on the renewable energy based clean power generation techniques to secure the environment from carbon effect. Among the development of renewable energy based power generation techniques the solar power generation has a major role of clean power generation. The sunlight is free of cost and everlasting energy sources, but the drawback of this method generation of electricity is only possible during sunshine. In this paper we have focused maximum power generation and maximum power injection to the distribution power grid (vide fig 1) [1]. The organization of this paper is as follows. Section II presents the modelling of Photovoltaic cell and its operation. In section III, details of the proposed MPPT controller are presented. The simulation model of the proposed system is presented in section IV and the simulation results are presented in section V. Finally the section VI concludes the paper.

II MATHEMATICAL DESIGN OF PHOTOVOLTAIC POWER SYSTEM

The following mathematical models of electrical characteristics are considered to design 400Wphotovoltaic module and simulated using the matlab environment as shown in fig4. The fig 5 and fig 6 presents the PV module, voltage and output power respectively of the proposed system. A. Open circuit voltage:

Voltage corresponds to the voltage drop across the diode (p-n junction), when it is transverse by the photocurrent Iph, (ie.) when the generated current I = 0 [2]. It reflects the voltage of the cell in the night and it can be mathematically expressed as:

Volt---------------(1)

Where : V is the open circuit voltage N is diode ideality constant K is the Boltzmann constant (1.381*10^-23 J/K) T is temperature in Kelvin Q is electron charge (1.602*10^-19 c) IL is the light generated current same as Iph (A) Io is the saturation diode current (A) B. Light generated current (Radiation):

------------ (2)

Where : G is the radiation (W/m2) Gref is the radiation under standard condition 1000 W/m2 ILref is the Photoelectric current under standard condition 0.15 A TCref is module temperature under standard condition 298 K αISC is the temperature co-efficient of the short circuit current (A/K)=0.0065/K IL is the Light generated current (Radiation) C. Reverse saturation current:

-------(3)

------------------- (4)

Where: Io is the Reverse saturated current Ior is the saturation current N is the ideality factor 1.5; Eg is the band gap for silicon 1.10ev D. Short circuit current: Ish = IL. It is the greatest value of the current generated by a cell. It is produced by the short circuit conditions: V = 0.


3968

--------------(4)

E. Irradiation: G=radiation W/m2. III MPPT CONTROLLER

The renewable energy sources play an

important role to meet consumer power demand due to their abundant availability and a smaller amount impact of environment. The main hurdle in PV energy expansion is the investment cost of the PV power system implementation. PV energy generation is not constant throughout the day due to the change of weather. The efficiency of power generation is very low ( the range of efficiency is only 9-17% in low irradiation regions) [3]. Therefore MPPT technologies have an important role in PV power generation to operate in the maximum power generation at various weather conditions [6]. The various MPPT methods are developed with respect to usage of equipment and cost.

A. Feedback voltage and current method This method mostly used in without a

storage Photovoltaic power system. PV panel actual output voltage and current values are compared with reference voltage and current value and the error calculated. The DC/DC converter duty cycle has a design based on error value and operates the PV panel near to MPP B. Voltage and Frequency (P-Q) method

In this method two different controllers are available to control inverter side and battery power management. Duty cycle for DC-DC converter is generated, by PI controller, with respect to change of PV power generation. C. Feedback of power variation with voltage and

current This method is similar to that of feedback

voltage and current method, in addition to this method monitoring the power variation with voltage or current ( ) or ( ) equal to zero under power

feedback [7]. In this method the power measured from load terminal not from a PV panel because power conversion loss is there due to the converter. Hence the duty cycle is adjusted for ( ) or ( )

achieving MPP. D. Perturbation and Observation

This method has to measure PV voltage and current at the present atmosphere condition the PV power P1, is calculated by considering the small

changes from duty cycle and the PV power P2 is calculated. The PV power P2 is compared with P1. The perturbation is taken as correct when P2 is more than P1, This method has a major drawback due to occasional deviations from the maximum [9]. E. Incremental conductance method

In this method the voltage and current value measured from PV cell. The above values are compared with a reference value based on error the controller has generated the duty cycle and fed to the PWM generator for inverter [10]. F. Proposed model intelligent control based MPPT method - In this method we have been designed fuzzy logic controller [2]. This controller has two inputs, namely, actual irradiation and PV voltage. Trapezoidal method is used to convert these parameters to fuzzy set. Knowledge based system has the reference voltage and compares the observed value [4]. Based on the error we have made IF-THEN rules for selecting duty cycle. Finally the fuzzy set value is converted into a crisp set using the centre of gravity method, and then the signal is fed into a PWM generator to generate the pulse for DC-DC converter [5].

Fig 1: Proposed Fuzzy based MPPT Controller

Fuzzy Control

Fig 2: Input fuzzy Membership function-PV Voltage

Fig 3: Input fuzzy Membership function - Irradiation


3969

Fig 3: output fuzzy Membership function - Modulation index ( duty cycle)

VI MATLAB SIMULATION AND RESULTS

Fig 4: Modelling of Photovoltaic cell

Fig 5: PV Module Voltage Waveform

Fig 6: PV Module Power Waveform without MPPT

Fig 7: Voltage generation waveform with respected to various irradiation


3970

Fig 8: Power generation waveform with respected to various irradiation

Fig 9: Simulation model of Fuzzy Logic control based MPPT for Photovoltaic power system

Fig 10: Photovoltaic Power curve with MPPT controller at various Irradiations


3971

Fig 11: Photovoltaic Voltage curve with MPPT controller at various Irradiations

V RESULTS DISCUSSION

A 400 WATTS PHOTOVOLTAIC MODULE: In this paper 400W PV panel is considered. Mathematical model illustrated in section II is simulated using the MATLAB environment as presented in fig 4. We have analysed the PV characteristics such as Voltage and power changes with respect to different weather conditions (6am to 6pm) as shown in fig 5 and fig 6 respectively. B FUZZY MPPT CONTROLLER: The proposed MPPT controller has two inputs and single output such as Irradiation and PV voltage are input signals and Duty cycle is output [8]. The input variables are converted into fuzzy membership function using the trapezoidal method as shown in fig 2 and 3. The duty cycle is an output membership function as presented in fig 4. The rules are developed with respect to the nature of changes in input and output variable to achieve the goal. C SIMULATION RESULTS: The proposed model is simulated in MATLAB background and observed. Results such as PV power, PV voltage, DC-DC boost converter Voltage, THD of system, DC-AC grid integration and Inverter output are analysed and tested with IEEE 1547 standard. Values obtained, by simulation, for PV power and PV voltage are shown in fig 5 and fig 6 respectively. PV power output is observed at different irradiation and temperature conditions and presented in fig 8 and fig 10. Variation of voltage and power from 6AM to 6PM is plotted in fig 7 and fig 11. Fig 12 points out the

PV single phase inverter output voltage (220V). The THD value is illustrated in fig 13.

Fig 12: single phase PV inverter output voltage

Fig 13: Proposed model THD value 1.06%

VI CONCLUSION

This paper presents the Photovoltaic

mathematical model used for simulation and analysis. The simulation results of the electrical characteristics under different irradiation and temperature environment are presented. The fuzzy


3972

based MPPT controller is developed in Matlab and simulated. The obtained results are evaluated and compared with IEEE 1547 standard. Effectiveness of the proposed MPPT controller is established and this controller is recommended for use in grid connected PV systems.

VII REFERENCE

[1].Adhikari, S.; Fangxing Li, "Coordinated V-f and P-Q Control of Solar Photovoltaic Generators With MPPT and Battery Storage in Microgrids," Smart Grid, IEEE Transactions on , vol.5, no.3, pp.1270,1281, May 2014 [2]. Wei Xu; Chaoxu Mu; Jianxun Jin, "Novel Linear Iteration Maximum Power Point Tracking Algorithm for Photovoltaic Power Generation," Applied Superconductivity, IEEE Transactions on , vol.24, no.5, pp.1,6, Oct. 2014 [3]. Feng Wang; Xinke Wu; Lee, F.C.; Fang Zhuo, "Analysis of unified output MPPT control in Sub-Panel PV converter system," Power Electronics and Applications (EPE), 2013 15th European Conference on ,

vol., no., pp.1,8, 2-6 Sept. 2013 [4]. Kumar, T.Praveen; Subrahmanyam, N.; Sydulu, M., "Fuzzy controlled power management strategies for a grid connected hybrid energy system," T&D Conference and Exposition, 2014 IEEE PES , vol., no., pp.1,5, 14-17 April 2014 [5].Ya-Ting Lee; Chian-Song Chiu;

Tse-Wei Chiu, "Maximum power point tracking of grid-tied photovoltaic power systems," Power Electronics Conference (IPEC-Hiroshima 2014 - ECCE-ASIA), 2014 International , vol., no., pp.440,445, 18-21 May 2014

[6]. Chokchai, C., "Power flow control and MPPT parameter selection for residential grid-connected PV systems with battery storage," Power Electronics Conference (IPEC-Hiroshima 2014 - ECCE-ASIA), 2014 International , vol., no., pp.3789,3795, 18-21 May 2014

[7]. Bakkar, M.; Abd El-Geliel, M.; Zied, M.A., "Control of photovoltaic grid connected using different control strategies," Control and Automation (MED), 2014 22nd Mediterranean Conference of , vol., no., pp.710,715, 16-19 June 2014 [8]. Kollimalla, S.K.; Mishra, M.K., "A Novel Adaptive P&O MPPT Algorithm Considering Sudden Changes in the Irradiance," Energy Conversion, IEEE Transactions on , vol.29, no.3, pp.602,610, Sept. 2014 [9]. Indumathi, R.; Venkateshkumar, M.; Raghavan, R., "Integration of D-Statcom based photovoltaic cell power in low voltage power distribution grid," Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on , vol., no., pp.460,465, 30-31 March 2012 [10].Anandhakumar, G.; Venkateshkumar, M.; Shankar, P., "Intelligent controller based MPPT method for the Photovoltaic power system," Human Computer Interactions (ICHCI), 2013 International Conference on , vol., no., pp.1,6, 23-24 Aug. 2013

VIII BIOGRAPHY

Dr. R. Raghavan, Obtained his BE in Electrical Engineering from REC Warangal, A.P., in 1965. After the completion of the Masters program in Power Systems Engineering at REC Warangal in 1967, He pursued higher education at Indian Institute of Technology (IIT), Kanpur and earned his Doctoral Degree (Ph.D.) in 1971.He has more than 40 years experience in R&D Power system . Presently he is working as an educational consultant. Email: [email protected]

M. Venkateshkumar, (Vice Chairman IEEE PES and Young Professional Madras Section) received BE in Electrical & Electronics Engineering from Anna University Chennai through E.G.S. P Engg college in 2007. He received ME in Power Systems Engineering from Vinayaka Missions University in 2009. He is Pursuing Ph.D at Sathyabama University Chennai. He has published technical papers more than 18 Technical papers in an International conferences and Journal & Review Board Member for than 12 International conferences and international journals. Reviewer of IEEE Transaction on sustainable Energy. Presently he is working as an Asst Professor (Senior Grade) in Dept of Electrical and Electronics Engineering at Saveetha School of Engineering, Saveetha University Chennai, Tamilnadu, India. His current research interest includes Grid integration of hybrid renewable energy sources. Email: [email protected]


3973

Documents

Intelligent Control Based MPPT for Grid Penetration of Photovoltaic power System